Process for generation of protein and uses therof

ABSTRACT

A method of generating a protein with an improved functional property, the method comprising:
         (a) identifying at least one Target amino acid Residue in a first protein, wherein said Target amino acid Residue is associated with said functional property;   (b) comparing at least one homologous second protein from the same or a different phylogenetic branch as the first protein with the first protein and identifying at least one Variant amino acid Residue between the first protein and the second protein;   (c) selecting at least one Candidate amino acid Residue from the Variant amino acid Residue identified in (b) on the basis of said Candidate amino acid Residue affecting said Target amino acid Residue with respect to said functional property;   (d) forming at least one Candidate Mutant protein in silico or producing at least one Candidate Mutant protein in vitro in which said at least one Candidate amino acid Residue from the second protein substitutes a corresponding residue in the first protein; and   (e) screening said at least one Candidate Mutant protein produced in (d) to identify a protein having said improved functional property.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of International ApplicationPCT/AU2007/001542, with an international filing date of Oct. 10, 2007,which claims the benefit of Australian Provisional Patent ApplicationNo. 2006905622, filed Oct. 10, 2006, and this application claims thebenefit of U.S. Provisional Application No. 61/045,552, filed Apr. 16,2008, all of which are hereby incorporated by reference in theirentirety.

FIELD OF THE INVENTION

The present invention relates to a process for the generation ofproteins with improved properties, in particular Rubisco proteins, anduses thereof.

BACKGROUND OF THE INVENTION

Ribulose-1,5-bisphosphate (RuBP) carboxylase/oxygenase is more commonlyknown by the abbreviation Rubisco. Rubisco is an enzyme participating incarbon fixation in the Calvin Cycle whereby atmospheric carbon dioxideis fixed and made available to biological systems in the form ofenergy-rich molecules.

In plants, algae, cyanobacteria and phototropic and chemoautotrophicproteobacteria, Rubisco comprises large subunit (LSU) chains and smallsubunit (SSU) chains. The substrate binding sites are located in thelarge chains. The large chains form dimers in which amino acids fromeach large chain contribute to the binding sites. A total of four largechain dimers and eight small chains assemble into a larger complex ofabout 540,000 Da.

Rubisco catalyzes the first step in photosynthetic CO₂ assimilation(carbon reduction), as well as the competitive fixation of O₂ whichproduces the waste product that is recycled in photorespiratory carbonoxidation. The importance of Rubisco is underlined by the fact that itis the major catalyst in the key chemical reaction by which inorganiccarbon enters biological systems. Furthermore, Rubisco is a veryabundant protein. Parry et al. (2003) suggest that Rubisco accounts for30-50% of total soluble protein in chloroplasts.

However, the relative abundance of Rubisco may be attributable to thefact that it is a very slow acting enzyme, which only fixes a few CO₂molecules per second, in contrast to the thousands of chemical reactionsper second characterizing many enzymes. The enzyme is inefficient as acatalyst for the carboxylation of RuBP and is subject to competitiveinhibition by O₂, to inactivation by loss of carbamylation, and todead-end inhibition by RuBP binding prior to activation of the enzyme bycarbamylation by CO₂. This nonoptimal behavior makes Rubisco ratelimiting for photosynthesis. Consequently, under most conditions andwhen light is not otherwise limiting photosynthesis, Rubisco is theprimary rate-limiting enzyme of the Calvin Cycle.

As Rubisco is often rate limiting for photosynthesis in plants, improvedforms of Rubisco would have considerable impact on increasingagricultural productivity. Several attempts have been made to increasethe efficiency of Rubisco-mediated reactions. Previous approachesinclude introducing constructs which express Rubisco from one organisminto another organism, increasing the level of expression of Rubiscosubunits, expressing Rubisco small subunits from the chloroplast DNA,and altering Rubisco genes by mutagenesis so as to try to increasespecificity for carbon dioxide (over oxygen) or otherwise increase therate of carbon fixation.

Attempts have been made to introduce foreign Rubiscos, for example thatfrom red algae such as Galdieria partita having a high CO₂/O₂specificity, into flowering green plants. This would have been expectedto improve the photosynthetic efficiency of crop plants, but theseattempts failed due to problems with production, assembly and regulationof the foreign Rubisco in the host plant (Spreitzer and Salvucci, 2002;Parry et al., 2003). On the other hand, the large subunit of tobaccoRubisco has been successfully replaced with the homologous large subunitof the simpler purple photosynthetic bacterium Rhodospirillum rubrumwhich does not require a small subunit to fold and assemble into anactive enzyme (Andrews and Whitney, 2003). While demonstrating thatRubisco replacement was achievable, the transgenic plant exhibited thevery inferior specificity and catalytic properties of R. rubrum Rubisco.

Numerous attempts to define the roles of the active-site residues inspecific steps of the reaction or to modify and improve the catalyticproperties of Rubisco have been made using site-directed mutagenesiscoupled with insights from X-ray crystallographic structures of Rubiscocomplexes from several species. However, these studies have failed toprovide a detailed and self-consistent definition of the various rolesof the residues of the active site over the complete reaction timecourse. These techniques have been uniformly unsuccessful in engineeringa “better” Rubisco. While one mechanism by which Rubisco operates may bededuced by these studies, it may not be unique due to different possibleinterpretations of the incomplete experimental data, and, thus, it maynot be the mechanism which exists in reality. For example, themechanisms proposed in the Cleland consensus mechanism for Rubiscoassume that a water molecule was displaced from the magnesium at theactive site before formation of the reactive complex for carboxylation,and that consequently all subsequent steps in the reaction also proceedon the assumption that this displacement takes place. However, there isno experimental evidence that water is in fact displaced.

This contrasts with re-engineering programs for many other enzymes wheresingle mutations, or in some cases multiple mutations, which werededuced straightforwardly from structural and mechanistic data obtainedexperimentally have proven successful in modifying substrate specificityor catalytic efficiency in predictable desired directions.

A major difficulty in implementing a rational re-engineering approachfor Rubisco is that none of the reported experimental studies hasprovided direct evidence of the structure for all the intermediatesinvolved, nor the precise roles of all the participating active-siteresidues, due to the aforementioned incompleteness of experimental data.Experimental approaches are inherently unable to define precise rolesfor protons and water molecules involved in catalytic processes, as theyare “invisible” to experimental probes. This difficulty is compounded bythe complexity both of the Rubisco active site and by the fact that asequence of reactions is involved. There is proposed to be a number ofactive-site “elements” comprising different combinations of active-siteresidues which take part in the different reactions steps, with theresidue groups often being “reused”.

It appears that current Rubiscos represent only “partial evolutionarysolutions” to optimizing the enzymic efficiency, i.e. that evolutionaryprocesses have been unable to sample effectively the LSU sequence space,and that these current solutions represent far-from-optimum solutions.Thus, there is an opportunity to create more optimum solutions by adifferent route, or combination of routes, than biological evolution hasbeen able to provide so far.

The creation or identification and introduction of more efficient formsof Rubiscos into photosynthetic organisms by transformation, selectivebreeding or other manipulations may allow more efficient growth of theseorganisms, including green plants and in particular flowering plants, asthey would make more efficient use of water and nitrogen, and may growmore efficiently at higher temperatures. This in turn offers prospectsfor better yielding crops, the revegetation of degraded or drought-proneland, improved options for carbon sequestration and improvements in theproduction of biofuel or biomass energy and so on.

In summary, there is a need for generating proteins, such as a Rubisco,having improved functional properties wherein, for example, suchproteins have improved efficiency and are adapted specifically forparticular environmental conditions.

SUMMARY OF THE INVENTION

The present inventors have hypothesised that extant Rubiscos havesampled only a fraction of the theoretically available mutational spaceto improve their efficiency and that different spaces may have beensampled by different groups of Rubiscos. Hence, they propose thecoupling of these partial evolutionary “solutions” by grafting featuresfrom more than one phylogenetic group, or from more than oneenvironmentally adapted species, onto a host Rubisco in order to gainthe benefits of wider evolutionary mutational sampling than has beenpossible naturally. They propose that this process will identifyRubiscos with improved efficiency or other functional properties.

According to a first aspect of the invention, there is provided a methodof generating a protein with an improved functional property, the methodcomprising:

(a) identifying at least one Target amino acid Residue in a firstprotein, wherein said Target amino acid Residue is associated with saidfunctional property;

(b) comparing at least one homologous second protein from the same or adifferent phylogenetic branch as the first protein with the firstprotein and identifying at least one Variant amino acid Residue betweenthe first protein and the second protein;

(c) selecting at least one Candidate amino acid Residue from the Variantamino acid Residue identified in (b) on the basis of said Candidateamino acid Residue affecting said Target amino acid Residue with respectto said functional property;

(d) forming at least one Candidate Mutant protein in silico or producingat least one Candidate Mutant protein in vitro in which said at leastone Candidate amino acid Residue from the second protein substitutes acorresponding residue in the first protein; and

(e) screening said at least one Candidate Mutant protein produced in (d)to identify a protein having said improved functional property.

In one embodiment, step (a) and step (b) may be performedsimultaneously.

In another embodiment, step (b) may be performed before step (a).

In one embodiment, the identification of at least one Target amino acidResidue in a first protein of step (a) may reduce the amount of sequencespace to be examined for the identification of Candidate amino acidResidues from the Variant amino acid Residues identified in step (b).

In one embodiment, step (d) comprises forming or producing at least oneCandidate Mutant protein by using the at least one Candidate amino acidResidue from the second protein to substitute a corresponding residue ina homologous protein and/or in homologous proteins other than or inaddition to the first protein.

In another embodiment, step (d) comprises forming or producing at leastone Candidate Mutant protein in which at least two Candidate amino acidResidues from the second protein substitute corresponding residues inthe first protein and/or in a homologous protein other than the firstprotein.

In one embodiment, the at least one Target amino acid Residue iscontained in a first protein or in a set of proteins containing thefirst protein.

In certain embodiments, the at least one Target amino acid Residue is atleast 2, at least 3, at least 4, at least 5, at least 10, at least 12,at least 15, at least 20, at least 30, or at least 50 Target amino acidResidues.

In one embodiment, the protein is an enzyme and the improved functionalproperty is selected from any one or more of improved kinetic efficiencyof the enzyme, an altered specificity of the enzyme for one or moresubstrates, an altered specificity for one or more products of theenzyme and an altered effective temperature range for enzyme catalysis.Where the protein is Rubisco, the improved functional property may beany one or more of improved carboxylation efficiency, improved k^(c)_(cat), improved K_(c), improved specificity (S_(c/o)), or improvedtemperature dependence. In particular embodiments the improvedfunctional property is a combination of any two or more of improvedcarboxylation efficiency, improved k^(c) _(cat), improved K_(c),improved specificity (S_(c/o)), or improved temperature dependence.

In one embodiment, the Target amino acid Residues are selected fromthose residues directly interacting with a substrate or a reactionintermediate, which include for example in Rubisco those residuesdirectly coordinating to the reaction centre (“first shell” residues),or directly coordinating with one or more of the aforesaid residues,(i.e. “second shell” residues). Where the protein is Rubisco, thefirst-shell residues of Rubisco may be selected from any one or more ofGlu60, Asn123, Lys175, LYS177, KCX201, Asp203, Glu204, His294 andLys334.

In one embodiment, the Target amino acid Residues of the Rubisco proteinare in the N-terminal domain of the Rubisco Large subunit. TheN-terminal domain Target amino acid Residues may be involved in thegas-addition step of carboxylase catalysis mediated by a Rubisco enzyme.In a particular embodiment, the N-terminal domain Target amino acidResidues involved in the gas-addition step are selected from the groupconsisting of ASN123, GLU60 and Tyr20.

In one embodiment the protein is an enzyme, and the second protein isselected on the basis of kinetic and functional features adapted forparticular growth environments, such as hot- or cold-adaptation, ordrought resistance. These features may be identified, for example, fromenvironmental diversity data for the second protein.

In yet another embodiment, the at least one Candidate amino acid Residueis identified as a residue being capable of affecting said at least oneTarget amino acid Residue identified in (a) and the at least oneCandidate amino Residue modulates the functional property of the formedprotein. The Candidate amino acid Residue may affect the at least oneTarget amino acid Residue with respect to the functional property due toproximity of the Candidate amino acid Residue to the at least one Targetamino acid Residue. For example, the effect may be due to steric,electrostatic or hydrophobic effects.

In certain alternative embodiments, step (c) comprises selecting atleast one Divergent Candidate amino acid Residue, instead of at leastone Candidate amino acid Residue, from the Variant amino acid Residuesidentified in (b). In particular embodiments, step (c) comprisesselecting at least 2 Divergent Candidate amino acid Residues.

In certain alternative embodiments, step (c) comprises selecting atleast one Alternative Candidate amino acid Residue, instead of at leastone Candidate amino acid Residue, from the Variant amino acid Residuesidentified in (b). In particular embodiments, step (c) comprisesselecting at least 2 Alternative Candidate amino acid Residues.

In other particular embodiments, step (c) comprises selecting at leastone Alternative Candidate amino acid Residue and at least one DivergentCandidate amino acid Residue instead of at least two Candidate aminoacid Residues, from the Variant amino acid Residues identified in (b).

In one embodiment, step (a) of identifying at least one Target aminoacid Residue comprises the step of active-site fragment QM calculationsand/or hybrid QM/QM and/or QM/MM calculations based on empirical data ofthe structure of the protein. In one embodiment, the empirical data isX-ray crystal structure or solution NMR structure. In one embodiment,the empirical data may further comprise any one or more of mutationaldata, kinetic data, isotope discrimination, calorimetric, andspectroscopic data (Fersht, 1998; Frey and Hegeman, 2007). In oneembodiment, the QM/MM calculations are complemented by moleculardynamics (MD) simulations with a QM/MM potential (Gready et al., 2006).

In one embodiment, the step of selecting at least one Candidate aminoacid Residue from the at least one Variant amino acid Residue comprisesassessing the proximity of the at least one Target amino acid Residueidentified in (a) to Variant amino acid Residues identified in (b)and/or relative position to secondary structural units.

The step (c) of selecting at least one Candidate amino acid Residue maycomprise identifying changes between said first protein and said secondprotein with respect to electrostatic and/or hydrophobic interactions ofthe one or more Variant amino acid Residue identified in (b) with the atleast one Target amino acid Residue identified in (a) and/or a secondarystructural unit which contains the at least one Target Residueidentified in step (a). Said selection procedure also comprisesidentification of compensatory mutations necessary to remove sterichindrance effects created by introducing a Candidate amino acid Residueinto the first protein.

In yet another embodiment, the step of screening the at least oneCandidate Mutant protein comprises any one or more of in silicoanalysis, biochemical assessment and physiological assessment. Thebiochemical assessment may include assessment of correct folding and/orassembly of the protein, assessment of the structure of the protein,assessment of the catalytic activity and/or other binding function ofthe protein or assessment of the stability of the protein in vitro. Thephysiological assessment may include assessment of correct expression,correct folding and/or assembly of the protein, assessment of thestructure of the protein, assessment of the catalytic activity of theprotein or assessment of the stability of the protein in vivo.

In yet another embodiment of the first aspect, the method also includesthe further step performed after step (c) and prior to step (d) ofgrouping Candidate amino acid Residues predicted as having a cumulativeeffect on said at least one Target amino acid Residue. For example saidcumulative effect may be effected via one or more of electrostaticand/or hydrophobic and/or steric effects, for example by coordinated orcompensating effects on positioning of secondary structural units andloops, which modify such effects.

In yet another embodiment, the method also includes the further stepperformed immediately after step (d) of ranking said Candidate Mutantproteins having said improved functional property. The process ofranking said Candidate Mutant proteins may comprise assessing theirlikelihood of having said improved functional property. This procedurecomprises assessing the relative potential contributions of Candidateamino acid Residues and/or Alternative Candidate amino acid Residuesand/or Divergent Candidate amino acid Residues in said Candidate Mutantproteins to said improved functional property.

In one embodiment, the first aspect comprises the additional step ofusing information derived from at least one round of screening CandidateMutant proteins in step (e) for the identification of Sub-regions withinthe protein structure that preferentially influence the properties ofTarget amino acid Residues linked to said Region.

In another embodiment, the Sub-regions may provide a basis foridentifying additional Candidate Residues, Alternative CandidateResidues, Co-variant residues and/or Divergent Candidate Residuespredicted to interact with Candidate Residues, Alternative CandidateResidues and/or Divergent Candidate Residues identified by steps (a) to(e). The rounds of screening may be used to generate a set of preferredmutational sites, and a preferred set of combinations thereof.

In yet another embodiment of the first aspect, the method comprises thefurther step of performing directed evolution on said protein havingsaid improved functional property and screening products thereof.

According a second aspect of the invention, there is provided a methodof generating a Rubisco protein with an improved functional property,the method comprising:

(a) identifying at least one Target amino acid Residue in a firstRubisco protein, wherein said Target amino acid Residue is associatedwith said functional property;

(b) comparing at least one second Rubisco protein from the same or adifferent phylogenetic branch as the first Rubisco protein with thefirst Rubisco protein and identifying at least one Variant amino acidResidue between the first Rubisco protein and the second Rubiscoprotein; (c) selecting at least one Candidate amino acid Residue fromthe Variant amino acid Residues identified in (b) on the basis of saidCandidate amino acid Residue affecting said Target amino acid Residuewith respect to said functional property;

(d) forming at least one Mutant Rubisco protein in silico or producingat least one Mutant Rubisco protein in vitro in which said at least oneCandidate amino acid Residue from the second Rubisco protein substitutesa corresponding residue in the first Rubisco protein; and

(e) screening said at least one Candidate Mutant Rubisco proteinproduced in (d) to identify a Rubisco protein having said improvedfunctional property.

In one embodiment, step (a) and step (b) may be performedsimultaneously.

In another embodiment, step (b) may be performed before step (a).

In another embodiment, the identification of at least one Target aminoacid Residue in a first protein of step (a) reduces the amount ofsequence space to be examined for the identification of Candidate aminoacid Residues from the Variant amino acid Residues identified in step(b).

In another embodiment of the second aspect, the residues of the secondRubisco protein used for comparison with the first Rubisco proteincomprise all residues directly coordinated to the active site of aRubisco protein, all residues interacting with the reactive centre ofthe substrate or intermediate reaction species of a Rubisco protein, andother residues within a proximate distance from the active site of aRubisco protein or a subset of such residues. For example the proximatedistance may be between 3 and 28 Å from any atom of substrate orintermediate reaction species. Typically the proximate distance isbetween 6 and 20 Å from any atom of substrate or intermediate reactionspecies. More typically, the proximate distance is between 9 and 15 Åfrom any atom of substrate or intermediate reaction species.

In one embodiment of the second aspect, the first Rubisco protein istaken from species of green plants and cyanobacteria and the secondRubisco protein is taken from species of red algae. In a particularembodiment the first Rubisco protein is taken from species of floweringplants and cyanobacteria and the second Rubisco protein is taken fromspecies of red algae.

In one embodiment of the second aspect, step (c) comprises selecting atleast one Divergent Candidate amino acid Residue, instead of at leastone Candidate amino acid Residue, from the Variant amino acid Residuesidentified in (b). In particular embodiments, step (c) comprisesselecting at least 2 Divergent Candidate amino acid Residues.

In certain alternative embodiments of the second aspect, step (c)comprises selecting at least one Alternative Candidate amino acidResidue, instead of at least one Candidate amino acid Residue, from theVariant amino acid Residues identified in (b). In particularembodiments, step (c) comprises selecting at least 2 AlternativeCandidate amino acid Residues.

In other particular embodiments, step (c) comprises selecting at leastone Alternative Candidate amino acid Residue and at least one DivergentCandidate amino acid Residue instead of at least two Candidate aminoacid Residues, from the Variant amino acid Residues identified in (b).

In one embodiment of the second aspect, there is provided a method ofpurifying the Rubisco protein, the method comprising the steps of:

(a) fusing into a first vector the coding sequence for a H₆ taggedubiquitin (Ub) sequence (H₆Ub) to the 5′ end of an rbcS gene;

(b) co-transforming the first vector with a second vector coding for thelarge subunit and small subunit of the Rubisco protein into a host;

(c) inducing expression of said Rubisco protein and vectors;

(d) purifying the Rubisco protein based on the expression of theubiquitin tag fused to the Rubisco small subunit;

(e) removing Ub fragments from the Rubisco.

In one embodiment, step (d) of purifying said protein is performed usingchromatography such as metal affinity chromatography.

In one embodiment, the first and/or second vector is a plasmid.

In one embodiment, the host is E. coli.

In one embodiment, the large subunit comprises one or more mutations.

In one embodiment, the Ub fragments are removed using a Ub-specificprotease.

According to a third aspect of the invention, there is provided aprotein produced by the method of the first or second aspects of theinvention.

According to a fourth aspect of the invention, there is provided aRubisco protein produced by the method of the first or second aspects ofthe invention.

According to a fifth aspect of the invention, there is provided aRubisco protein which comprises the sequence as set forth in any one ofSEQ ID NOS: 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 50, 52, 54,56, 58, 60, 62, 64, 66, 68, 70, 74, 76, 78, 80 or a functionalequivalent thereof.

According to a sixth aspect of the invention, there is provided aRubisco protein encoded by a polynucleotide comprising the sequence setforth in any one of SEQ ID NOS: 25, 27, 29, 31, 33, 35, 37, 39, 41, 43,45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 73, 75, 77, 79 or afunctional equivalent thereof.

According to a seventh aspect of the invention, there is provided aRubisco large subunit polypeptide comprising one amino acid residuesubstitution or a combination of amino acid residue substitutionsselected from the group consisting of (Y25W, D51I), (Y25W, D51V), (T23G,K81R), (G54A, C84A, 187V), (G54S, C84A, 187V), (T23G, Y25W, D51I,K81R),), (T23G, Y25W, E51I, K81R), (Y25W, D51I, G54A, C84A, 187V),(Y25W, D51I, G54S, C84A, 187V), (Y25W, D51V, G54A, C84A, 187V), (V121I,M297G, V300T), (L36I, I116L, F140L), (L36I, I116L, V121I, F140L, M297G,V300T), (K18I, T23G), (K21A, L22K, (gap)M, T23G, Y25W), (T23G, K18I,T68V, K81R), (T23G, K81R, P104E), (T23G, D19P, K81R), (T23G, K81R,V121I, M297G, V300T), (T23G), (K81R), (V121I, M297G), (M297G), (V121I).

In one embodiment, the Rubisco large subunit is present in a Rubiscoprotein. In one embodiment, the Rubisco is provided in the form of afusion protein or a fragment which retains the biological activity ofthe Rubisco.

Also provided is a polynucleotide which encodes a Rubisco LSUpolypeptide according to the seventh aspect.

Also provided is a vector which comprises the polynucleotide sequence ofthe fifth aspect or the polynucleotide sequence defined in sixth aspect.

In one embodiment the vector comprises a constitutive or selectableexpression promoter. In one embodiment, the vector comprises aselectable marker.

According to a eighth aspect of the invention, there is provided a hostcell transformed with a nucleic acid sequence or the vector according tothe above aspects.

In one embodiment, the host cell is a prokaryotic cell or a eukaryoticcell. In certain embodiments, the prokaryotic host cell is a bacterialcell such as E. coli.

According to a ninth aspect of the invention, there is provided aphotosynthetic organism transformed with a nucleic acid sequence or avector of one of the above aspects. In one embodiment, thephotosynthetic organism is a cyanobacterium.

In another embodiment, the photosynthetic organism is a Synechococcus,such as Synechococcus sp. PCC7942 or Synechococcus sp. PCC6301.

In one embodiment the photosynthetic organism is a flowering plant. Theflowering plant may be a wild type or transgenic tobacco (Nicotianatabacum). The transgenic tobacco may be a tobacco in which nativetobacco rbcL has been replaced by rbcM from Rhodospirillum rubrum.

In one embodiment, the protein is expressed in photosyntheticorganelles.

In yet another embodiment, the organelle is a plastid.

In yet another embodiment, the organelle may be chosen from the group ofplastids of photosynthetic eukaryotes comprising chloroplast(chlorophyll-containing plastid), etioplast (chloroplast not exposed tolight), chromoplast (non-chlorophyll-containing plastid), or leucoplast(non-pigmented plastids for storing starch (amyloplast), lipid(elaioplast) or protein (proteinoplast)).

According to a tenth aspect of the invention, there is provided a methodof increasing photosynthetic efficiency of an organism, the methodcomprising introducing a nucleic acid sequence which encodes a Rubiscoprotein according any one of the above aspects into said organism andexpressing the Rubisco protein.

According to a eleventh aspect of the invention, there is provided amethod of increasing crop yield, the method comprising introducing anucleic acid sequence encoding a Rubisco protein of one of the aboveaspects into said crop plant.

According to a twelfth aspect of the invention, there is provided amethod of increasing drought resistance in a plant wherein said methodcomprises introducing a nucleic acid sequence encoding a Rubisco proteinaccording to one of the above aspects into said plant.

According to a thirteenth aspect of the invention, there is provided amethod of increasing biomass in one or more plants or otherphotosynthetic organism(s), wherein said method comprises introducing anucleic acid sequence encoding a Rubisco protein according to one of theabove aspects into said plant(s) or organism(s).

According to a fourteenth aspect of the invention, there is provided amethod of producing a biofuel comprising material from a plant or plantsor other photosynthetic organism(s), wherein said method comprisesintroducing a nucleic acid sequence encoding a Rubisco protein accordingto one of the above aspects into said plant(s) or organism(s).

In one embodiment of the tenth to fourteenth aspects, the introductionof proteins may comprise the step of transformation, sexualreproduction, or a combination thereof.

ABBREVIATIONS

-   aadA plasmid gene conferring resistance to streptomycin and    spectinomycin-   ACR Alternative Candidate Residue-   2CABP 2-carboxyarabinitol 1,5-bisphosphate-   2C3KABP 2-carboxy-3-ketoarabinitol 1,5-bisphosphate-   3-PGA 3-phospho-D-glycerate-   CM Candidate Mutant-   CPK model Corey-Pauling-Koltun space-filling molecular    representation of spherical atoms with radii proportional to the    atom's van der Waals radius-   CR Candidate Residue-   CvR Co-variant Residue-   DCR Divergent Candidate Residue-   DFT density functional theory-   ESP electrostatic potential-   FM fragment model-   H₆ 6× histidine affinity tag-   K_(c) ^(0%) Rubisco Michaelis constant (K_(m)) for CO₂ at 0% oxygen-   K_(c) ^(air) Rubisco Michaelis constant (K_(m)) for CO₂ at 21%    (ambient) oxygen-   k^(c) _(cat) Rubisco carboxylation turnover rate-   k^(c) _(cat)/K_(c) ^(air) Rubisco carboxylation efficiency-   k_(cat) turnover rate of an enzyme-   K_(m) Michaelis constant of an enzyme-   k_(cat)/K_(m) catalytic efficiency of an enzyme-   K_(o), or K_(io) Rubisco Michaelis constant (K_(m)) for O₂-   LSU Large subunit-   MD molecular dynamics-   PDB code Protein Data Bank identity number-   ONIOM Our owN n-layered Integrated molecular Orbital+molecular    mechanics Method-   QM quantum mechanical-   QM/MM hybrid quantum mechanical/molecular mechanical-   QM/QM hybrid quantum mechanical/quantum mechanical-   rbcL polynucleotide encoding a Rubisco large subunit-   rbcLS polynucleotide encoding a Rubisco large subunit of    Synechococcus sp.-   rbcLS-rbcSS (or rbcL-S) polynucleotide encoding a Rubisco large    subunit and Rubisco small subunit of Synechococcus sp.-   rbcM polynucleotide encoding the Form II Rubisco from Rhodospirillum    rubrum-   rbcS polynucleotide encoding a Rubisco small subunit-   rbcSS polynucleotide encoding a Rubisco small subunit of    Synechococcus sp.-   RuBP Ribulose-1,5-bisphosphate-   Rubisco Ribulose-1,5-bisphosphate carboxylase/oxygenase-   S_(C/O) Rubisco specificity for CO₂ compared with O₂ defined as    (k^(c) _(cat)/K_(c) ^(0%))/(k^(o) _(cat)/K_(o))-   SSU Small subunit-   SsVR Species-specific Variant Residue-   TIM barrel a protein domain structure first defined in    triosephosphate isomerase-   TR Target Residue-   TS transition state-   Ub ubiquitin-   V_(c) ^(max) extrapolated maximal Rubisco carboxylase activity-   VR Variant Residue

DEFINITIONS

As used in this application, the singular form “a”, “an” and “the”include plural references unless the context clearly dictates otherwise.For example, the term “a plant cell” also includes a plurality of plantcells.

As used herein, the term “comprising” means “including.” Variations ofthe word “comprising”, such as “comprise” and “comprises,” havecorrespondingly varied meanings. Thus, for example, a polynucleotide“comprising” a sequence encoding a protein may consist exclusively ofthat sequence or may include one or more additional sequences.

By “host cell” is meant a cell which contains an introduced nucleic acidconstruct and supports the replication and/or expression of theconstruct. Host cells may be prokaryotic cells such as E. coli, oreukaryotic cells such as algae, fungi, yeast, insect, amphibian,nematode, plant or mammalian cells. The host cells may be plant cells,such as monocotyledonous plant cells or dicotyledonous plant cells. Anexample of a host cell is an E. coli host cell.

The term “green plant” as used herein is intended to encompass organismsincluding, but not necessarily limited to, unicellular or multicellularorganisms from the Divisions Pteridophyta (ferns), Bryophyta (mosses),Charophyta and Chlorophyta (aquatic green algae), Magnoliophyta(flowering plants or angiosperms), and Pinophyta (conifers).

As used herein, “homologous” proteins are proteins which share anevolutionary origin. Homologous proteins may share the same essentialfunction (orthologous proteins) or may exhibit significantly different,evolutionarily diverged, functions (paralogous proteins).

As used herein, “nucleic acid” means a polynucleotide and includessingle or double-stranded polymer of deoxyribonucleotide orribonucleotide bases. Nucleic acids may also include fragments andmodified nucleotides.

As used herein “operably linked” includes reference to a functionallinkage of at least two sequences. Operably linked includes linkagebetween a promoter and a second sequence, wherein the promoter sequenceinitiates and mediates transcription of the DNA sequence correspondingto the second sequence. The rbcL-S is an example of an operably linkedsequence.

As used herein, “photosynthesis” refers to the process in green plantsand certain other organisms by which carbohydrates are synthesized fromcarbon dioxide and water using light as an energy source. Most forms ofphotosynthesis release oxygen as a byproduct.

As used herein, “phylogenetic branch” refers to a group oflineage-connected organisms. In the context of the present invention,phylogenetics constitutes a means of classifying groups of organismsaccording to degree of evolutionary relatedness. A phylogenetic branchmay contain organisms of different taxonomic divisions, class, order,family, genus or species.

“Phylogenetic grafting” refers to the process of introducing at leastone amino acid residue of a donor protein from an organism of onephylogenetic branch into a recipient protein from an organism of adifferent phylogenetic branch for the purpose of improving thefunctional properties of the recipient protein. Phylogenetic graftingmay be carried out by substituting at least one amino acid residue intoa given position in the sequence of a recipient protein, the at leastone amino acid residue being at the same position in the second donorprotein selected on the basis of the phylogenetic analysis.

As used herein, “plant” includes plants and plant parts including butnot limited to plant cells, plant tissue such as leaves, stems, roots,flowers, and seeds.

As used herein, “promoter” includes reference to a region of DNA that isinvolved in recognition and binding of an RNA polymerase and otherproteins to initiate transcription.

As used herein, “protein” refers to any polymer of amino acids linkedthrough peptide bonds or modified peptide bonds, whether producednaturally or synthetically. The protein of the invention may comprisenon-peptidic components, such as carbohydrate groups. Carbohydrates andother non-peptidic substituents may be added to a protein by the cell inwhich the protein is produced, and vary with the type of cell. Proteinsare defined herein, in terms of their amino acid backbone structures;substituents such as carbohydrate groups are generally not specified,but may be present nonetheless.

As defined herein, the “function” of a protein refers to the normal rolefor the protein in the cell, or a role for which a protein may beengineered to carry out. In one embodiment the protein is an enzyme.Where the protein is an enzyme, the function may be the catalysis of atleast one chemical reaction. In other embodiments the function may bestructural (e.g. serving as a cytoskeletal protein). The function mayinvolve the active or passive transport of a substance within the cellor between the cell interior and exterior, or between differentcompartments within the cell, or between different regions of theorganism, for example where the protein is involved in a channel or amembrane pore, or the protein is involved in trafficking of materials tospecific cellular compartments or the protein acts as a chaperone or atransporter. The function may be involved with ligand/receptorinteractions, for example where the protein is a growth factor, acytokine, a neurotransmitter or an intracellular or extracellularligand, or the protein is a receptor for the growth factor, cytokine,neurotransmitter or the intracellular or extracellular ligand.

Where the protein is an enzyme, the enzyme may be involved in catabolismor metabolism. The enzyme may be involved in the synthesis of at leastone product. The enzyme may be involved in the breakdown of at least onesubstrate. The enzyme may be involved in the chemical modification of atleast one substrate, for example the addition or deletion of one or morephosphate groups from a molecule. The enzymes may be involved indegradation of at least one substrate.

Thus, a “functional property” of a protein is a property whichcontributes to the function of the protein. For example where a proteinis an enzyme, the functional property may be the specificity of theenzyme for a particular substrate, the kinetic efficiency of the enzyme,its effective temperature range for catalysis, or its specificity forcatalysing its normal reaction and minimizing side-reactions to unwantedand/or potentially toxic byproducts.

The term “residue” in the context of a polypeptide refers to anamino-acid unit in the linear polypeptide chain. It is what remains ofeach amino acid, i.e —NH—CHR—C—, after water is removed in the formationof the polypeptide from α-amino-acids, i.e. NH₂—CHR—COOH.

The terms “Target amino acid Residue” or “Target Residue” (TR) refer toan amino acid residue which is identified and/or predicted to contributedirectly to the function of the protein. Where the protein is an enzyme,the contribution of a Target Residue to the functional property may be adirect influence of the Target Residue on the catalytic reaction(s)carried out by the enzyme at one or more of the enzyme's active site(s),via direct interaction or involvement in the active site. A TargetResidue will not be distant from an enzyme active site. Where theprotein is a receptor, the Target Residue will be directly involved inthe receptor site. In the methods described herein, a Target Residue maybe identified by computational and/or molecular simulation methods, asthese methods are able to consider positions of water molecules,protons, ionisation states and hydrogen bonds associated with the TargetResidues in the enzyme active site, or receptor site, which are notunambiguously definable by experiment. In the methods of the presentinvention, it is anticipated that the mutation of the Target Residueswould in general lead to a disruption or reduction of function.Accordingly in the methods of the present invention, the Target Residuesare not directly altered by substitution with another amino acid, butrather the properties of the Target Residues such as their position andcharge are “tuned” by the manipulation of one or more residues whichinteract with the Target Residues.

The terms “Variant amino acid Residue” or “Variant Residue” (VR) referto a specific amino acid residue of a second protein or a specific aminoacid residue identified in a consensus sequence of a plurality of secondproteins which is identified as being different from the correspondingamino acid residue found in a first protein which is homologous to thesecond protein. Variant Residues may be identified, for example, usingan alignment of the amino acid sequences of the first and secondproteins. The sequences of the first and/or second proteins may beconsensus sequences. The sequences may be derived from organisms of thesame or of a different phylogenetic branch. For the Rubisco largesubunit, it is rare for there to be sequence additions or deletionsbetween the sequences of different organisms, apart from in the N- orC-terminal regions which are not important for the catalytic function ofRubisco. Nevertheless, for the purposes of the present invention, in oneembodiment a Variant amino acid Residue may be a residue which ispresent in a first protein but absent in a second protein, or which isabsent in a first protein but present in a second protein.

The terms “Candidate amino acid Residue” or “Candidate Residue” (CR)refer to an amino acid residue from a second protein which is selectedfrom amongst a plurality of Variant Residues and which is suspected ofbeing able to influence one or more Target Residues sterically and/orelectrostatically, and thereby influence the function of the proteinmediated by the one or more Target Residues. A Candidate Residue is aresidue which may be selectively transplanted into a first protein of ahost in order to attempt to modulate the functional activity of thefirst protein towards the desired functional activity of the secondprotein.

In some embodiments, the Candidate Residue may be selected on the basisof commonality and/or difference of amino acid residues between two ormore phylogenetic branches. In the context of selecting CandidateResidues for Rubisco, a Candidate Residue is one which is suspected ofbeing able to influence one or more Rubisco Target Residues stericallyand/or electrostatically, for example by modifying the chargedistribution over the Target Residue and/or by modifying the spatialposition of the Target Residue and/or by modifying the ability of theTarget Residue to move.

Where the protein is Rubisco, the Candidate Residue may be present inthe consensus sequence from red algae but different in the correspondingresidue position in the consensus sequences from flowering plants andcyanobacteria, and at a position where the amino acid is the same inflowering plants and cyanobacteria. In particular embodiments, theCandidate amino acid Residue may be chosen from the residue present inred algae.

Where the protein is Rubisco, identification of a Candidate Residue asone suspected of affecting the gas-addition step allows it to bedifferentiated from other Variant Residues showing non-conserved changesbetween branches or sub-branches, which may represent neutralphylogenetic drift, or which may have a branch-specific physiologicalrole, such as in folding, assembly, including interactions with thesmall subunit, or stability.

The terms “Divergent Candidate amino acid Residue” or “DivergentCandidate Residue” (DCR) refer to an amino acid residue which isselected from amongst a plurality of Variant Residues and which issuspected of being able to influence one or more Target Residuessterically and/or electrostatically, and thereby influence the functionof the protein mediated by the one or more Target Residues. TheDivergent Candidate Residue is selected on the basis of difference ofamino acid residues at a given position in the consensus sequence of theprotein among at least three phylogenetic branches. For example, in thecontext of selecting Divergent Candidate Residues for Rubisco, aDivergent Candidate Residue is one which is suspected of being able toinfluence one or more Rubisco Target amino acid Residues stericallyand/or electrostatically, and which may be present in the consensussequence from red algae but different in the corresponding residue fromthe consensus sequence of flowering plants and the consensus sequence ofcyanobacteria, and also different at the corresponding residue from theconsensus sequence of flowering plants and the consensus sequence ofcyanobacteria. The Divergent Candidate Residue may be selected from thesequence or consensus sequence from the protein of any one of thephylogenetic branches which were compared.

The terms “Alternative Candidate amino acid Residue” or “AlternativeCandidate residue” (ACR) refer to an alternative amino acid at theposition of a Candidate Residue which is expressed in a second protein,but which is not the amino acid which is expressed in the consensussequence of the second protein. Thus an Alternative Candidate Residueprovides a residue which is expressed at the given position in at leastone species of the second protein but which is not expressed in themajority of sequences from the same phylogenetic branch. Where theprotein is Rubisco, an ACR may be selected, for example, from thesequence of Griffithsia monolis Rubisco which exhibits a significantlyhigher catalytic rate than a Rubisco from a typical red algal species.

The terms “Co-Variant amino acid Residue” or “Co-Variant Residue” (CvR)refer to a residue which is identified in the sequence of a secondprotein from a particular species, as being in the vicinity of anAlternative Candidate Residue and showing complementary variation to theAlternative Candidate Residue. This variation of the Co-Variant Residue,which is not present in the consensus sequence for the second protein,may be suspected to reflect complementary changes in the structuraland/or electrostatic properties of the Alternative Candidate Residue andCo-Variant Residue. Identification of Co-Variant Residues provides ameans to identify auxiliary residue positions which may be mutated inthe first protein to better accommodate changes made from transferringAlternative Candidate Residues.

The terms “Species-specific Variant amino acid Residue” or“Species-specific Variant Residue” (SsVR) refer to residues which varyamong closely related species of a protein. In conjunction withassociated functional data for each variant protein, SsVRs may be usedto map sequence-structure-function relationships. These correlations maybe used to predict which variable residues might be contributing most tothe improvement in the desired property for the protein. This SsVRinformation may be used in conjunction with the general method toidentify CRs. Predictions of a Candidate Mutant protein containinggroups of residues may include SsVRs in addition to the CRs, ACRs, DCRsor CvRs which more directly affect Target Residues.

The terms “Candidate Mutant protein” or “Candidate Mutant” (CM) refersto a mutant protein in which at least one or groups of two or more CRsand/or ACRs and/or DCRs, with optional additional CvRs or SsVRs, arecombined into a single protein.

The term “Region” refers to a division of the protein structuresurrounding the Target Residues which may be made on the basis ofproximity of a particular Target Residue or Target Residues toparticular parts of the reactive centre or binding site. A Regioncomprises a spatially contiguous volume of protein structure containingsubsets of CRs, DCRs, ACRs, CvRs and SsVRs which may preferentiallyinfluence the interactions of a particular Target Residue or TargetResidues with particular parts of the reactive centre or binding site.The boundaries of Regions are not precisely defined. Regions may haveoverlapping segments of protein structure. The purpose of definingRegions is to facilitate the application of the phylogenetic graftingmethod by loosely identifying the subsets of CRs, DCRs, ACRs, CvRs andSsVRs which may be grouped to form Candidate Mutants. For example, wherethe protein is Rubisco, a region labelled Region 1, which comprises mostof the large subunit N-terminal domain and several small segments ofstructure from the C-terminal domain of the adjacent large subunit, maybe identified as being able to influence the Target Residues Asn123,Glu60 and Tyr20, which specifically interact, directly or indirectly,with the nascent carboxylate group of the reactive species during thegas-addition step.

The term “Sub-region” refers to a division of a Region which may be madeon the basis of proximity of a particular Target Residue or TargetResidues to a component part of the Region. A Sub-region comprises aspatially contiguous volume of protein structure containing a subset ofthe Region's CRs, DCRs, ACRs, CvRs and SsVRs which are predicted topreferentially influence the properties of the particular Target Residueor Target Residues linked to the Region. The boundaries of Sub-regionsare not precisely defined. Sub-regions may have overlapping segments ofprotein structure. Defining Sub-regions may facilitate the applicationof the phylogenetic grafting method by loosely identifying the subsetsof the Region's CRs, DCRs, ACRs, CvRs and SsVRs which may bepreferentially grouped to form Candidate Mutants. For example, where theprotein is Rubisco, component regions of Region 1, labelled 1A, 1B and1C, may be identified, which are predicted to preferentially influencethe properties of Target Residues Tyr20, Asn123 and Glu60, respectively.

The term “sequence space” broadly refers to the set of all possiblesequences of residues for a polymer of specific length. For example, thecomplete sequence space for a protein or polypeptide of 100 amino acidresidues in length is the set of all sequences consisting of allpossible variations of the 100 amino acids. If single mutations areconsidered only, then the sequence space for a protein or polypeptide of100 amino acid residues in length is 100 times 19 (for the 20 amino acidresidue set). A reduction in the sequence space of a protein orpolypeptide of given length will, therefore, reduce the number ofpossible sequences of amino acid residues in a set of protein orpolypeptide mutants. In the context of the present invention, theindependent identification of Target amino acid Residues and Variantamino acid Residues produces two different reduced sets of sequencespace to be examined. The subsequent intersection of these sets effectedwhen the Target amino acid Residues are used to identify Candidate aminoacid Residues from Variant Residues further reduces the sequence spacefor consideration. Accordingly, the number of residues of the proteinand their combinations which need to be considered for mutation arethereby greatly reduced.

A kinetic parameter is associated with a value. Jointly the kineticparameter and its value define the magnitude of a functional property.In the case of Rubisco, a kinetic parameter may be but need not belimited to, for example, carboxylation efficiency, or a value for k^(c)_(cat), or a value for K_(c), or a value for specificity (S_(c/o)), or avalue for temperature dependence.

The term “kinetic profile” refers to a set of kinetic parameters andtheir associated values for an enzyme. For example a kinetic profile fora Rubisco may refer to a set of parameters with values for a singleRubisco mutant which show changes in the values of certain kineticparameters over the wild type Rubisco.

The term “Rubisco phenotype” refers to a particular combination of keykinetic parameters (such as specificity, carboxylation efficiency, andtemperature dependence) and their associated values.

As used herein, the term “directed evolution” refers to methods aimed atmodifying the function and/or structure of target protein/s. In general,directed evolution is a process by which proteins are “adapted” to actin different or existing natural or artificial chemical or biologicalenvironments and/or to elicit new functions and/or increase or decreasea given activity, and/or to modulate a given feature.

BRIEF DESCRIPTION OF THE FIGURES

The present invention will now be described by way of example withreference to the accompanying figures.

Flowchart 1 provides a flowchart of the Rubisco re-engineering strategy,highlighting the roles of computational chemistry and bioinformatics inproviding the mechanistic, sequence, structural and phylogeneticinformation which is integrated by the phylogenetic grafting procedureto produce the in silico predictions of Candidate Mutant proteins. Thisintegration provides a means by which the Target Residues may be used toselect out Candidate Residues from Variant Residues, thereby greatlyreducing the number of residues of the protein, and their combinations,which need to be considered for mutation towards improvement of thefunctional property. Candidate Residues, as shown in the middle column,may optionally comprise ACRs and/or DCRs. These procedures are shown inmore detail in Flowchart 2. The prediction steps are followed byexperimental screening and assessment of improvement of the functionalproperty. The results may be fed back into the prediction procedure torefine the predictions of Candidate Mutant proteins, followed by furthercycles of computational and experimental screening and assessment ofimprovement of the functional property, to optimize the protein'sactivity. The dotted-line boxes represent optional extensions to thecore phylogenetic grafting procedure which are shown in an expanded formin Flowchart 3.

Flowchart 2 provides a flowchart detailing the prediction strategy forthe phylogenetic grafting method, showing the integration of thecomputational chemistry with the bioinformatics analysis to produce theranked list of Candidate Mutant proteins. This procedure involves stepsof selecting Variant Residues against Target Residues to produceCandidate Residues (which optionally may comprise ACRs and/or DCRs),grouping and combining groups of Candidate Residues (and/or DivergentCandidate Residues or Alternative Candidate Residues), and ranking thegroups and combined groups to produce a ranked list of Candidate Mutantproteins for optional computational pre-screening and experimentalscreening.

Flowchart 3 provides a flowchart which details an optional extension ofthe method for phylogenetic grafting, in which a list of CandidateResidues is assessed and assembled into Candidate Mutants, and thenfurther Candidate Residues, Alternative Candidate Residues, DivergentCandidate Residues, Co-variant Residues and Species-specific VariantResidues may be recruited and grouped, based on their influence onTarget Residues, and formed into new refined Candidate Mutants.

Flowchart 4 provides a summary of a strategy for reduction of thesequence space of the Rubisco LSU which may be considered for predictingCandidate Mutants. Step 1 represents the starting point of 475 residues(open squares) in the LSU. In step 2, the five Target Residues (filledsquares) that are most involved in the gas-addition reactions areidentified by computational chemistry. In step 3, the approximately 130Variant Residues (filled circles) that may encode superior functionalproperties of Rubisco are identified by bioinformatic analysis. In step4, the 26 Candidate Residues (shown by *) are selected from the VariantResidues based on their potential to influence the Target Residues. Thecandidate sites for mutation are shown specifically numbered in 5. Instep 6, the Candidate Residues are grouped using bioinformatic analysisto form Candidate Mutants; some of those in Table 3 are shown.

FIG. 1 provides an illustration of the molecular structures involved inthe proposed reaction mechanism for the conversion of RuBP to twomolecules of 3-PGA at the Rubisco active site. The five steps ofenolization, carboxylation, hydration, C2-C3 bond scission and C2protonation are shown. The Roman numerals correspond to the intermediateand product species shown in FIGS. 3 and 4. Group R=—CH(OH)—CH₂—O—PO₃²⁻.

FIG. 2 illustrates the molecular structure for the 77-atom fragmentmodel of the Rubisco active site designated FM20 which was used for abinitio QM computational chemistry studies of the reaction pathway. Itshows the molecular-fragment species which were used to represent theLYS175, LYS177, ASP203, GLU204, KCX201 (carbamylated LYS201), HIS294,and LYS334 amino acid residues, the water molecule, the carbon dioxidemolecule, and the 4-carbon fragment of the enediolate form of thesubstrate RuBP. In addition, it shows the charge states of the componentspecies, and their interactions, namely the six atoms co-ordinated tothe Mg atom, hydrogen bonds and the van der Waals interaction betweenCO₂ and C2.

FIGS. 3A to 3E provides a series of molecular structures calculatedusing ab initio QM methods for the FM20 fragment model shown in FIG. 2.These show geometries of local minima along the reaction pathway fromenediolate to the end products in the Rubisco carboxylase reaction.Hydrogen atoms of the Mg-coordinated water molecule are highlighted byblack circles. Relevant distances for each structure which demonstratechanging interactions between component species as the reaction proceedsare shown through labels. Labels on some structures may be obscured.Label “d” refers to R_(KCX201-H . . . O) ₂, “i” refers toR_(Ow . . . C3), “j” refers to R_(H2O[Mg]-Hw1 . . . O-GLU204) and “k”refers to R_(H2O[Mg] . . . Hw1). The Roman numerals correspond to theintermediate, transition-state and product species shown in FIG. 4.

FIG. 4 provides a graph illustrating the potential energy surface forthe carboxylation and subsequent reactions in the carboxylase pathwaycomputed using ab initio QM computational chemistry calculations on thefragment model with 77 atoms (FM20). Different stages of the progress ofthe carboxylase reaction are distributed along the X-axis. The Romannumerals along the reaction pathway designate the starting (I)intermediate (III, V, VII) and product states (IX) of the carboxylasereaction shown in FIG. 1, and their connecting transition states (II,IV, VI, VIII). The structures of all these states are shown in FIG. 3.Energies (in kcal/mol) of all states are shown relative to that of thestarting enedioloate state I, and transition state energies relative tothe starting or relevant intermediate state are shown by Ea and anarrow.

FIGS. 5A to 5D provides a sequence alignment of the Rubisco LSU aminoacid sequences from photosynthetic organisms belonging to thirteendifferent phyla covering red algae, cyanobacteria, glaucophyta andplants (10 phyla), using single letter amino acid symbology. Thesesequences are also provided as SEQ ID NOS: 1-13. Where more than oneRubisco sequence was available in a phylum, a 50% consensus sequence wasused to represent that phylum. For the consensus sequences, the numeralin brackets represents the number of genera whose sequences were used togenerate the consensus sequence. The database accession numbers for allsequences used in the alignment are given in Table 1. The figure showsthat the Rubisco LSU sequence is highly conserved, including the almostcomplete absence of gaps except for minor differences at the N- andC-termini, and codes for a long polypeptide chain of 475 residues(plants and cyanobacteria). The symbol “˜” denotes sequence gaps. Thesingle-letter uppercase letters denote the amino acid residue alphabet,while lowercase letters and other symbols are shown in positions inconsensus sequences where only the type of residue is conserved: “h”,hydrophobic (A, C, F, G, H, I, K, L, M, R, T, V, W, Y); “s”, small (A,C, D, G, N, P, S, T, V); “u”, tiny (A, G, S); “a”, aromatic (F, H, W,Y); “c”, charged (D, E, H, K, R); “1”, aliphatic (I, L, V); “p”, polar(C, D, E, H, K, N, Q, R, S, T); “o”, alcohol (S, T); “t”, turnlike (A,C, D, E, G, H, K, N, Q, R, S, T); “−”, negatively charged (D, E); and“+” positively charged (H, K, R). The consensus sequences were obtainedusing the server at http://coot.embl.de/Alignment//consensus.html. Thealignment was corrected around the gap position near CR T271 (alignmentposition 273) based on structural comparisons between the x-raystructures for spinach (pdb 8ruc), Synechococcus (pdb 1rb1) and Galdieripartita (pdb 1bwv) complexes with Mg²⁺ and 2CABP. The SEQ ID NOS for thestructures are 17, 16 and 14, respectively, as shown in Table 1. Thenumbers at the ends of the lines denote the sequence number. The evenlyspaced numbers at the top are alignment markers, while the numbers inbold denote the sequence number for spinach.

FIGS. 6A and 6B provides 50% consensus sequences of Rubisco LSUs fromred algae (rhodophyta; 9 species), cyanobacteria (11 species) andflowering plants (magnoliophyta; 134 species). These sequences arepresented in the sequence listing as SEQ ID NOS: 2, 3 and 11,respectively, as shown in Table 1. Light grey shading indicates the 134residues that are the same in flowering plants and cyanobacteria butdifferent in red algae, i.e. the Variant Residues. Gaps in the sequenceare shown by “˜”. The definitions of uppercase and lowercase letters and“−” and “+” symbols are the same as in FIG. 5. The numbers at the endsof the lines denote the sequence number. The evenly spaced numbers atthe top are alignment markers, while the numbers in bold denote thesequence number for spinach.

FIGS. 7A and 7B provide 50% consensus sequences of Rubisco LSUs from redalgae (rhodophyta; 9 species), cyanobacteria (11 species) and floweringplants (magnoliophyta; 134 species), the same sequences shown in FIG. 6.Positions where the amino acid residues are conserved among all threeconsensus sequences are shown by the single-letter symbol for red algae(top line) and dots in lines for cyanobacteria and plants. Positionswhere the amino acid residue is the same for either cyanobacteria andplants as for red algae, are shown by the single-letter symbol for redalgae (top line) and dots in lines for either cyanobacteria or plants.Positions where the amino acid residue is the same in cyanobacteria andplants but different in red algae, i.e. the 134 Variant Residues shownin FIG. 6, are shown by the single-letter symbol for red algae (topline) and the single-letter symbol for cyanobacteria (second line),while the residue position has a blank space for plants (third line).Reverse shading highlights those VR positions which were selected asCandidate Residues for Region 1, as shown in Table 2, and which weregrouped into predicted Candidate Mutants, as shown in Tables 3 and 4.Positions where the amino acid residues are different in all threeconsensus sequences are shown by the single-letter symbols in all threelines, with grey shading highlighting those positions selected asDivergent Candidate Residues for Region 1, as shown in Table 2, andwhich were grouped into predicted Candidate Mutants, as shown in Tables3 and 4. The symbol “˜” denotes sequence gaps. Definitions of uppercaseand lowercase letters and “−” and “+” symbols are the same as in FIG. 5.The numbers at the ends of the lines denote the sequence number. Theevenly spaced numbers at the top are alignment markers, while thenumbers in bold denote the sequence number for spinach.

FIG. 8 provides a lateral view of the structure of the C-terminal TIMbarrel (residues 151-475) of one LSU polypeptide and the N-terminaldomain (residues 1-150) of an adjacent LSU which comprise the unitharbouring one active site of Rubisco. It shows the positions of theTarget Residues, E60, N123 and Y20 for Region 1, H294 for Region 2 andK334 for Region 3. This structure was drawn using atom co-ordinates fromthe complete L₈S₈ hexadecameric x-ray structure of wild-type spinachRubisco in the complex with Mg²⁺ and 2CABP (pdb 8ruc). 2CABP is shown asa CPK model. Residues E60 and N123 are located in helix αB and near theC-terminal end of helix αC, respectively, of the N-terminal domain. Theside chains of these two residues are located on either side of thecarboxylate group of 2CABP. Helices αB and αC have hydrophobicinteractions with the β-strands of the N-terminal domain. Y20 is locatedon single-coil structure near the N-terminal end of βA. Both K334 andH294 are located in the C-terminal domain which contains most of thefirst-shell residues of the active site. K334 is in loop 6, whereas H294is in β5.

FIG. 9 provides a view of the structure of the N-terminal domain of theRubisco LSU polypeptide (using co-ordinates from the spinach x-raystructure 8ruc) with the sidechains of the mutated residues (G23, R81,W25 and 151) for Mutant #6 (T23G, Y25W, D51I^(Gp), K81R), and thecomponent Mutants #4 (T23G, K81R) and #1a (Y25W, D51I^(Gp)), modelled inas stick models. See Table 3 for Mutant definitions. It shows therelative positions of these residues in the structure, and theinteractions between residues 25 (W25) and 51 (I51), and betweenresidues 23 (G23) and 81 (R81). The mutations add a hydrophobicinteraction between residues W25 and 151, compared with the wildtype Y25and D51, and remove a hydrogen-bonding interaction between residues 23and 81 (wildtype T23, K81 to mutant G23, R81). Severally or incombination, these two double mutations are predicted to alter theorientation of residue Y20. The positions of the Target Residues Y20,E60 and N123 are shown for reference as ball-and-stick models, while thereaction intermediate mimic 2CABP is shown in wire-model form.

FIG. 10 provides a view of the structure of the N-terminal domain of theRubisco LSU polypeptide (using co-ordinates from the spinach x-raystructure 8ruc) with the sidechains of the mutated residues (W25, I51,A54, A84, V87) for Mutant #7a (Y25W, D51I^(Gp), G54A^(Gp), C84A, 187V),and the component Mutants #1a (Y25W, D51I^(Gp)) and #5a (G54A^(Gp),C84A, 187V), modelled in as stick models. The figure illustrates theformation of a hydrophobic region by mutations at sites 54 (G→A), 84(C→A) and 87 (I→V). Additionally, if wildtype G54 was mutated toS54^(Gm) instead of A54GP (Mutant #7b, #5b), then an extra hydrogen bondwith the backbone of residue 51 is predicted to be introduced. In turn,151 has a hydrophobic interaction with residue W25. All these changesare predicted to affect the positioning of Target Residue Y20, shown inball-and-stick form. The positions of the other Region 1 Target ResiduesE60 and N123 are shown for reference as ball-and-stick models, while thereaction intermediate mimic 2CABP is shown in wire-model form. Forreference, the positions of the mutations for Mutant #4 (G23, R81) arealso shown.

FIG. 11 provides a view of the N-terminal domain of the Rubisco LSUpolypeptide (using co-ordinates from the spinach x-ray structure 8ruc)with the sidechains of the mutated residues (V^(Gp) or I^(Gm)36, L116,I121, L^(Gp) or I^(Gm)140, G297, T300) for Mutant #10a (L36V, I116L,V121I, F140L, M297G, V300T) and other Mutant #10 Gp/Gm variants(#10b,c,d), and the component Mutants #8 (V121I, M297G, V300T) and #9a(L36V, I116L, F140L) and other Mutant #9 Gp/Gm variants (#9b,c,d),modelled in as stick models. Residues A296 and V271 which are notmutated are also shown as stick models. To facilitate understanding ofthe changes in interactions predicted to result from the mutations, theRHS boxed inset shows the corresponding residues in wild typeSynechococcus as stick model. The figure illustrates the predicteddisruption of a hydrophobic interaction between residues V300, M297 andV121 in wild type to form a new hydrophobic interaction between A296,V271 and I121 in the Mutant (#8 or #10a). The prediction is based onstructural comparisons between the x-ray structures for spinach (pdb8ruc), Synechococcus (pdb 1rb1) and Galdieri partita (pdb 1bwv)complexes with Mg²⁺ and 2CABP. A new hydrophobic interaction betweenresidues 36, 140 and 116 is also predicted by the mutations L→V, F→L andI→L. Severally or in combination, these new hydrophobic interactionsmediated by these groups of mutations are predicted to affect theposition and orientation of Target Residue N123, which is shown inball-and-stick model. The positions of the other Region 1 TargetResidues E60 and Y20 are shown for reference as ball-and-stick models.

FIG. 12 provides a stereo view of the N-terminal domain of the spinachRubisco LSU (using co-ordinates from the spinach x-ray structure 8ruc).The side chains of all the N-terminal residues are shown in wire-framemodel. Target Residues (Y20, E60 and N123) are shown in stick model. Thecarboxylated-intermediate analogue 2CABP and Mg²⁺ are shown asball-and-stick models. The figure shows a complete 3-D representation ofall the residue sidechains of the N-terminal domain from which areselected CRs which are predicted to influence the TRs Y20, E60 and N123,as shown in FIG. 13. For reference, the orientation of the structure isthe same as in FIG. 15.

FIG. 13 provides a stereo view of the N-terminal domain of spinachRubisco LSU (using co-ordinates from the spinach x-ray structure 8ruc),with the 20 Candidate Residues and 6 Divergent Candidate Residues listedin Table 2 shown as stick models and the Target Residues labelled N123,E60 and Y20. The figure shows a complete 3-D representation of the CRand DCR sidechains in the N-terminal domain which are predicted toinfluence the TRs Y20, E60 and N123, as well as a small segment from theC-terminal domain of the partner LSU showing CRs M297 and V300 which arealso predicted to influence these TRs. Residues labelled T23 and K81 arethose which are mutated in Mutant #4 (T23G, K81R), while the residueslabelled Y25 and E51 are additionally mutated in Mutant #6 (T23G, Y25W,D51I^(Gp), K81R).

FIGS. 14A and 14B provide an amino acid sequence alignment of 50%consensus sequences of the N-terminal domain of Rubisco LSUs fromflowering plants (magnoliophyta; 134 species), cyanobacteria (11species), and red algae (rhodophyta; 9 species), as well as sequences ofseveral plants (spinach, tobacco, rice, soybean and sugarcane),Synechococcus sp. PCC6301 and red algae (Galdieri partita andGriffithsia monolis) species of special interest. The sequencespresented in this figure are also set out in SEQ ID NOS 2, 3 and 11,used previously in FIGS. 5-7, and 14-21. These are listed with databaseaccession numbers in Table 1. The full sequence is shown insingle-letter and symbol form for the cyanobacteria consensus (see FIG.5 for an explanation of the symbols), with amino acid residues in othersequences shown by dots if conserved or by the single-letter/symbolformat if not conserved. The numbers at the ends of the lines denote thesequence number. The evenly spaced numbers at the top are alignmentmarkers, while the numbers in bold denote the sequence number forspinach. Black reverse shaded vertical strips highlight the 17 currentCandidate Residues (i.e. those residues common between 50% consensussequences from flowering plants and cyanobacteria but different in redalgae) in the N-terminal domain: residues 18, 19, 23, 25, 51, 54, 59,64, 68, 81, 84, 87, 88, 104, 114, 118, 121. Grey shaded vertical stripshighlight the 6 current Divergent Candidate residues (i.e. thoseresidues which differ in green plants, cyanobacteria and red algae):residues 36, 86, 116, 117, 138, 140.

FIG. 15 provides a view of the N-terminal domain and segments of theC-terminal domain of the adjacent subunit of spinach Rubisco LSU (usingco-ordinates from the spinach x-ray structure 8ruc). At the bottom theβ-keto reaction intermediate (2-carboxy-3-ketoarabinitol1,5-bisphosphate (2C3KABP); III; see FIG. 1), Mg²⁺ and other residuesfrom the C-terminal domain of the partner LSU co-ordinated in thefirst-shell of the active site (see FIG. 2) and their disposition to theTarget Residues Y20, E60 and N123. Y20, E60, N123 and the β-ketoreaction intermediate are shown as thick-stick models, while theactive-site residues are shown in thin-stick model. The figure showsSub-region 1A in the N-terminal domain and Sub-region 1B in theN-terminal domain and segments of the C-terminal domain of the adjacentsubunit. Sub-region 1A includes the positions of CR 18 and new CRs 19,68 and 104 which are expected to improve Mutant #4 (T23G/K81R) ifmutated in combinations (#17-1A (#4+K18I/T68V), #18-1A (#4+P104E(D)),#19 (#4+D19P)) and further combinations thereof. Subregion 1B includespositions in the new Candidate Mutant #20-1B(V116L/L117T/V121I/I138M/F140L) containing DCRs 116, 117, 138 and 140,CR 121, and totally conserved residue 135.

FIGS. 16A and 16B provide a graphic with an expanded view ofinteractions in Candidate Mutant #20-1B (V116L/L117T/V121I/I138M/F140L)in Sub-region 1B. Panel A shows for reference the complete N-terminaldomain, positions of TRs N123, E60 and Y20 and the active-site centre(2CABP, Mg²⁺), and helix C and strand E. Panel B shows how the componentresidues 116, 117, 120, 121 and 135, 138 and 140 located on helix C andstrand E interact, and how changes to these interactions are predictedto influence the nearby TR N123; another view is in FIG. 17. 2CABP andMg²⁺ are shown in CPK model. N123, E60 and Y20 are shown in thick-stickmodel.

FIG. 17 provides a graphic of the N-terminal domain of the Rubisco LSUand segments of the C-terminal domain of the adjacent subunit as aribbon model showing the relative positions of all the three Subregions,1A, 1B and 1C, and some of the CRs and DCRs in these Subregions. Some ofthe key predicted interactions used in designing Region 1 CandidateMutants are shown by lines connecting CRs and DCRs.

FIG. 18 provides a structural model used in ONIOM QM/QM calculationsundertaken with DFT as the high layer and semiempirical QM (PM3)) as thelow layer. The DFT layer (shown as large ball and stick model) comprises93 atoms including fragments of all residues in the first coordinationshell of the active site and substrate: the magnesium atom (Mg²⁺),enediolate of RuBP, GLU60, ASN123, LYS175, LYS177, carbamylated LYS201,ASP203, GLU204, HIS294, LYS334. This core layer is surrounded by afurther 711 atoms in the PM3 (semi-empirical QM) layer, which comprisesamino acid residues up to ˜12 Å from Mg²⁺. The starting co-ordinateswere taken from the X-ray structure of the spinach Rubisco-2CABP complex(pdb 8ruc). The size of the entire system is 804 atoms.

FIG. 19 provides a graphic showing the core structure of the Rubiscoactive site and the division of the structure surrounding the TargetResidues into three spatially contiguous Regions. Region 1 comprisesamino acid residues that can influence the TRs GLU60, ASN123 and TYR20and comprises the N-terminal domain and small segments of the C-terminaldomain of the adjacent subunit. Regions 2 and 3 are in the C-terminaldomain and comprise amino acid residues that can influence the TRsHIS294 and LYS334, respectively.

FIG. 20 provides a gel showing the separation of R. rubrum L₂ Rubiscoand tobacco L₈S₈ Rubisco by non-denaturing polyacrylamideelectrophoresis. Soluble leaf protein from wild-type tobacco, tobaccoMutant #4 and tobacco Mutant #23-1B lines used for the kineticsmeasurements was separated by non-denaturing polyacrylamideelectrophoresis and visualised by Coomassie staining. The L₂ Rubiscothat is present in the ΔaadA tobacco-rubrum line (tr) and in theheteroplasmic tobacco Mutant #4 transformant line #4 (i.e. it producesboth L₂ and mutated L₈S₈ Rubiscos) is not present in the other tobaccoMutant lines or wild-type tobacco transformant. Marker proteins withsizes are indicated (m). The amount of soluble leaf protein loaded perlane is shown.

FIG. 21 provides a plot demonstrating the dependence of the rate of CO₂assimilation by plant leaves on the kinetic properties of wildtypetobacco Rubisco. The two lines show the rate under Rubisco limited(solid line) or electron-transport limited (dotted line) conditions,given by equations for A_(c) and A_(j), respectively, with the observedrate shown by the thick solid line. In the equations for A_(c) andA_(j), C is the chloroplast CO₂ partial pressure in μbar, Γ• is the CO₂compensation point (38.6 μbar), V_(cmax) is the substrate saturated rateof carboxylation (80 μmol m⁻²s⁻¹), K_(c) ^(0%) is the Michaelis constantfor CO₂ at 0% O₂ (260 μbar), O is the O₂ partial pressure (200 mbar),K_(o) is the Michaelis constant for O₂ (179 mbar), R_(d) is the day(non-photorespiratory) respiration (1 μmol m⁻² s⁻¹), and J is the rateof electron transport (variable in units of μmol m⁻² s⁻¹). Thetemperature and irradiance values used in the model are 25° C. and 1000μmol quanta m⁻² s⁻¹, respectively. The plot shows that the rate isRubisco-limited and electron-transport limited at lower and higher CO₂concentrations, respectively. The boxed region shows that most relevantto the CO₂ concentrations likely to be experienced in the leafintercellular space. The position of the intersection of the lines forA_(c) and A_(j), shown by *, with respect to the boxed region indicateswhich limiting conditions will be relevant over the accessible range ofCO₂ concentrations. As shown in FIGS. 22-24, this position varies withgrowth conditions and Rubisco phenotype. The arrowed lines show thedependence of the actual intercellular CO₂ concentration, C_(i), withatmospheric CO₂ concentration, C_(a), on stomatal conductance (given bythe equation −g=A/(C_(a)−C_(i))), which reflects the extent of openingof the leaf stomates to allow CO₂ to enter (and water to escape).Increased stomatal closure leading to lower C_(i) values is shown byarrowed lines of decreasing slope. At leaf internal CO₂ concentrationsof C_(i)(1) and C_(i)(2) at values of ˜230 and 300 μbar, whichcorrespond to stomatal conductances representing drought and averagewater-use conditions, respectively, the carbon assimilation rates are A₁and A₂. The method and parameter values are based on von Caemmerer(2000).

FIG. 22 provides plots demonstrating the predicted dependence of therate of CO₂ assimilation by plant leaves on different limiting growthconditions, using the kinetic properties of wildtype tobacco Rubiscoshown in FIG. 21. The position of the intersection of the lines forA_(c) and A_(j) is shown by *. Panel A: limiting water; values of ˜230and 300 μbar correspond to stomatal conductances representing drought(C_(i)/C_(a)=0.6) and average water-use (C_(i)/C_(a)=0.8) conditions,respectively (von Caemmerer, 2000). Panel B; limiting nitrogen; modelledby varying Rubisco content (100%, 60%, 30%). Panel C; limiting light;modelled by varying irradiance I (1000, 1600 and 400 μmol quanta m⁻²s⁻¹) Panel D; increasing temperature (25, 35 and 15° C.). Kineticparameters at different temperatures were obtained using equation 2.32from von Caemmerer (2000).

FIG. 23 provides plots comparing the predicted rate of CO₂ assimilationby plant leaves for examples of mutant tobacco Rubisco phenotypesshowing hypothetical improvements for an increase of 25% in one of thekey kinetic parameters (S_(c/o), k^(c) _(cat), K_(c)) with that forwildtype tobacco Rubisco. Plots are shown for variable temperature,light and Rubisco content (N content), as for FIG. 22, with wateravailability shown by the boxed regions. Full and dotted lines are forwildtype and mutant, respectively. In cases where no dotted line isvisible the wildtype and mutants lines overlay. The position of theintersection of the lines for A_(c) and A_(j) is shown by *. The boxedregion of each plot is that most relevant to the CO₂ concentrationslikely to be experienced in the leaf intercellular space. Panel A:effect of 25% improvement in specificity S_(c/o); Panel B: effect of 25%improvement in k^(c) _(cat); Panel C: effect of 25% improvement inK_(c).

FIG. 24 provides plots comparing the predicted rate of CO₂ assimilationby plant leaves for three different Rubisco phenotypes modelled fromkinetic data given in Tables 6 and 7. Plots are shown for variabletemperature, light and Rubisco content (N content), as for FIG. 22, withwater availability shown by the boxed regions. Full and dotted lines arefor wildtype and mutant, respectively. In cases where no dotted line isvisible the wildtype and mutants lines overlay. The position of theintersection of the lines for A_(c) and A_(j) is shown by * for wildtypeand ♦ for mutant, with points for the latter being circled for normalgrowth conditions. The boxed region of each plot is that most relevantto the CO₂ concentrations likely to be experienced in the leafintercellular space. Panel A: predictions for tobacco mutant #4 withkinetic profile {S_(c/o)=−4%; k^(c) _(cat)=+13%; K_(c)=+10%;K_(o)=+87%}. Panel B: predictions for tobacco mutant #23-1A with kineticprofile of {S_(c/o)=−6%; k^(c) _(cat)=+9%; K_(c)=+30%; K_(o)=+92%}.Panel C: predictions for tobacco mutant #6a with kinetic profile of{S_(c/o)=−18%; k^(c) _(cat)=+9%, K_(c)=+5%; K_(o)=+89%}.

DETAILED DESCRIPTION OF THE INVENTION

The present invention provides a method of generating a protein with animproved functional property. The invention comprises a procedure tonarrow the sequence space for conventional mutational test by definingmutants with one or, preferably, multiple mutations using mechanistic(computational) and bioinformatic and database(phylogenetic-specific/environment-specific sequence changes, kineticdata, 3-D structure and modelling) information, in the first instance. Asummary of how the problem of reduction of sequence space may be solvedby certain embodiments of the invention is illustrated for Rubisco inFlowchart 4. The procedure seeks to maximize the use of all availableinformation, particularly partial evolutionary adaptations encoded inRubisco sequences, so that the protein improvement process for therequired functional property starts at a functional level closer to therequired level of functional efficiency.

A first step of the method comprises the process of identifying Targetamino acid Residues in a first protein. As described in more detailbelow, the process of identifying Target amino acid Residues maycomprise active-site fragment QM calculations (step (i) using, forexample, DFT methods), and hybrid QM/QM or QM/MM calculations (step (ii)using, for example, ONIOM methods), in conjunction with use of empiricaldata (for example, kinetic data and X-ray crystal structures). Moleculardynamics (MD) simulations (step (iii)), and calculations usingcombinations of QM, QM/QM or QM/MM, and MD methods (steps (iv) and (v))may be used, respectively, for evaluating the stability of the predictedCandidate Mutant proteins, or for more detailed understanding of theroles of the Target Residues in the enzymic reaction. These Target aminoacid Residues will usually be cornerstone residues for the properfunctioning of the protein with respect to the functional property underinvestigation. It is a preferred feature of the invention that theimproved functional property is achieved by modifying the chemicalproperties of these residues (by mutation of other residues) in order toimprove, for example, their kinetic activity.

Convention for Numbering of Rubisco Amino Acid Residues

Throughout this specification, when identifying a residue of a RubiscoLSU by number, the residue numbering was based on the numbering of theresidue from the amino acid sequence of spinach Rubisco LSU (SEQ ID NO:17). This numbering convention was used for all residues identified incomputational chemistry, in protein structures and in mutations. Thisdoes not create ambiguity as these numbers can be mapped to sequencenumbers on alignments and from structural comparisons, and accordingly agiven spinach residue number can be mapped with total confidence to astructurally equivalent cyanobacterial or red algal residue number.

Sequence Listings

Table 1 provides a summary of the naturally occurring and 50% consensusRubisco amino acid sequences discussed herein and which are provided inthe computer-readable sequence listing, with the SEQ ID NOS as shown inthe “SEQ ID” column. Where multiple sequences were used to produce a 50%consensus sequence, the total number of sequences involved in theconsensus sequence creation is listed in brackets in the “Description”column. The database accession numbers provide unique identifiers foreach of the sequences which were used, including those sequences whichwere considered in the creation of consensus sequences. The numbers ofthe figures in which the sequences are used in alignments is also givenin the “Figure Nos” column.

TABLE 1 Database accession numbers for Rubisco LSU Sequences used inFIGS. 5, 6, 7 and 14. The Sequence ID numbers correspond to those in thecomputer-readable sequence listing. SEQ ID FIG. NO: Description NosDatabase accession number(s) 1 Protista glaucophyta 5 P24312 2 Protistarhodophyta (9) 5, 6, BAA75676 AAB17222 BAA75796 AAR13681 7, 14 ABU53651BAE78417 CAB58236 AAD04746 BAE78409 3 Eubacteria 5, 6, P00879 4008564104797620 402041420 cyanobacteria (11) 7, 14 5199140 P27568 403124030Q8DIS5 4296100 403238160 P00880 4 Plantae 5 Q31795 anthocerotophyta 5Plantae bryophyta (28) 5 Q95G53 Q76GQ2 Q5TM96 Q75W61 Q76GQ0 Q50L57Q5TMB1 Q75W60 Q76HL3 Q5TM93 Q9BB41 Q95G63 Q94N80 Q5TMA1 Q9TM58 Q75VP7Q8HW62 Q8SN97 Q95G62 Q9TM63 Q5TM99 Q5TMA5 Q9GIF5 Q5TMA3 Q5TM97 Q9GGM2Q5TM95 NP_904194 6 Plantae charophyta(4) 5 Q8SN66 P48716 Q32RY7 Q32RQ1 7Plantae chlorophyta(4) 5 NP_958405 BAE48225 AAD00447 BAC06367 8 Plantaeconiferophyta 5 P41621 9 Plantae equisetophyta 5 P48702 10 Plantaegnetophyta 5 Q9THI3 11 Plantae magnoliophyta 5, 6, Q3T5C7 Q5EKM0 Q95EI0Q06021 (134) 7, 14 Q31857 Q9MRW9 Q3V6P6 Q9GDM8 Q3V6M3 Q31670 O63085Q3T5G3 Q51221 Q06022 Q37167 AAF78948 Q6R615 Q3T5C1 P48688 Q06023 P48690Q75VD8 Q42664 Q7YKF9 Q9XQE3 Q9XPK2 Q8WJD8 P48693 Q5EKL6 O63123 Q8SLM3Q7YKF8 CAA57001 Q42674 P92255 Q98530 Q9XQB9 Q6R613 Q32072 Q3T575 Q9XQE7Q5EKM4 Q8WLJ3 Q95F13 Q3L237 Q5EKM2 P92287 Q37319 Q33449 Q9ZT30 Q32188Q9SB16 Q9BBC7 P19161 P48703 CAB08877 Q9GGC1 Q42828 Q4VWN7 Q5XLF7 Q95F23Q3T5G1 Q95BC5 Q95F12 Q32488 Q5EKL5 AAK72524 Q01873 Q75VD6 Q9BBU1 Q32518Q95EH6 Q9GHT6 Q8WIB0 Q32622 Q9MVF1 Q42916 O98611 Q5EKL8 Q3T5E7 Q32685NP_054507 Q5C9P7 BAA00147 Q9GHS0 Q68RZ8 Q3T5F6 Q7YL87 Q37257 Q36849Q95F15 Q95F24 Q95A48 Q32916 P04717 Q8WGU4 Q9XK53 Q9XQA7 Q32820 Q8ME88Q5MB28 Q5EKL2 Q8M962 Q75VD3 Q98612 Q8WKT8 Q6R614 Q9MTS7 Q8WIA8 Q95F20AAX44985 O62943 Q8WIC4 P48715 ABB90049 Q9XQ93 Q9GHN0 Q3T5E2 Q33064Q37281 Q8WIC3 Q9XPK3 Q6R617 Q8LUX7 Q8WKR2 AAP92166 Q6USP5 Q3T5E4 P28459Q95F10 P92364 CAA60294 Q75VD7 NP_054944 12 Plantae pinophyta(2) 5 P26961P26962 13 Plantae pteridophyta(2) 5 Q85WR7 Q33015 14 Galdieria partita14 BAA75796 15 Griffithsia monolis 14 ABU53651 16 Synechococcus 14P00880 elongatus PCC6301 17 Spinach (Spinacia 14 NP_054944 oleracea) 18Tobacco (Nicotiana 14 NP_054507 tabacum) 19 Rice (Oriza sativa) 14BAA00147 20 Soybean (Glycine max) 14 YP_538747 21 Sugarcane 14 BAD27301(Saccharum officinarum)

Identification of Target Residues—Computational Mechanism

Steps (i) and (ii) hereafter relating to the identification of Targetamino acid Residues were performed using the GAUSSIAN program package,for ab initio QM and ONIOM calculations (Frisch et al., 2004), but thereare several other proprietary or free-to-use programs available whichmight be used alternatively. Step (iii) uses the generally availableAMBER program (Case et al., 2006) to perform protein MD simulations;this capability is also available in many other programs. Steps (iv) and(v) employ published theory, protocols and programs for enzyme mechanismsimulations (Gready et al., 2006); the core semi-empirical QM/MM MDsimulation methods (Cummins and Gready, 1997, 1998, 1999, 2003, 2005;Cummins et al., 2007) are implemented in the program MOPS (Cummins,1996).

(i) Active-Site Fragment-Complex QM Calculations

The following description relates to calculations in respect of theRubsico LSU, in which active-site residues are totally conserved betweenspecies. These calculations use a high level ab initio QM method(B3LYP/6-31G(d,p)) to define the energetics and structures of thereaction species (substrate, transition-state (TS), intermediate, andproduct complexes) in the multi-step Rubisco reaction mechanism, asshown in FIG. 1. Computations were performed for the reaction stepsstarting from the gas-addition reaction, using the Gaussian 03 suite ofprograms (Frisch et al., 2004) and with starting co-ordinates taken fromthe X-ray structure of the spinach Rubisco-2CABP complex (pdb 8ruc). Theactive-site fragment model, FM20 as shown in FIG. 2, was large enough tocontain all the residues and water molecules immediately interactingwith the reaction centre and the coordinated Mg atom in the active site,and to allow definition of their roles in the different reaction steps,including the key gas (CO₂ or O₂) addition steps. The structures of thereaction species and the reaction energy pathway for the carboxylationand subsequent reaction steps are shown in FIGS. 3 and 4, respectively.

(ii) ONIOM Hybrid QM/QM and QM/MM Calculations:

These calculations define the perturbations to the energetics andstructures of the reaction-pathway species, and mainly focused on thegas-addition step from the next nearest neighbours and beyond of theactive-site residues. This was done using methods which use a high, butcomputationally expensive, ab initio QM model for the system core (i.e.as in (i)) and a less expensive QM (semi-empirical QM) or MM model foran extended region.

The calculations (QM/QM and QM/MM) were performed at several stagesusing the ONIOM module in GAUSSIAN 03. The ONIOM QM/QM calculations useda model of a high-level ab initio QM core layer of 93 atoms. For studyof the starting point at the gas-addition step, the QM core layercomprises the magnesium atom (Mg²⁺), enediolate of RuBP (to compute thestructure and energies of subsequent reaction species the correspondingRuBP-derived chemical species were used), GLU60, ASN123, LYS175, LYS177,carbamylated LYS201, ASP203, GLU204, HIS294 and LYS334. The core layeris surrounded by a further 711 atoms in the outer layer computed at thePM3 (semi-empirical QM) level, which comprises amino acid residues up to˜12 Å from the magnesium atom. The starting co-ordinates were taken fromthe X-ray structure of the spinach Rubisco-2CABP complex (pdb 8ruc).This model is illustrated in FIG. 18. The role of these calculations isto compare the effects of grafted residues in the vicinity of the activesite with those of the wild type on the energetics and structures of thereaction-pathway species, mainly focussed on the gas-addition step.These calculations allowed the structures and energies of the 93-atomactive-site fragments of the reaction species, analogous to those forthe QM FM20 model shown in FIGS. 3 and 4, to be re-optimized in theenvironment of surrounding enzyme residues (the 711-atom outer layer),and, thus, allowed perturbations to the energy profile of the reactiondue to grafted residues to be estimated. These calculations may thusprovide valuable insights on perturbations to the basic mechanism of, inthis case, wild-type spinach Rubisco to be determined, and, inparticular, the details of the structure of bound CO₂ and the nascentcarboxylate group in the gas-addition step. By these means, themagnitude and direction of electrostatic perturbations of theinteractions of Target Residues with reaction species due to graftedresidues in Candidate Mutants, can be calculated. This information maybe used to pre-screen Candidate Mutants for experimental test and/orused in interpretation of experimental test results, as shown inFlowchart 1, left hand column.

(iii) Molecular Dynamics (MD) Simulations of Protein Complexes

These simulations assessed whether the protein structure of graftedRubisco Candidate Mutants could accommodate the changed residues, i.e.whether the mutant protein structure was conformationally stable orwhether it tended to unravel. MD simulations are particularly useful formultiply-grafted mutants, and provide a global stability screening testto complement the electronic tests on the chemical mechanism from (ii).

These calculations were performed with the AMBER8 or AMBER9 programpackage (Case et al., 2006), but other protein MD simulation packages(e.g. GROMACS) could be used to obtain similar results.

(iv) Multiple ONIOM Hybrid QM/QM or QM/MM Calculations of DifferentSampled Conformational States of Complexes

In this method a series of calculations is undertaken using coordinatesfor protein complexes (e.g. for different reaction steps) taken fromsnapshots of trajectories of QM/MM MD simulations, as described byGready et al. (2006). These calculations allowed a more detailedexamination of features of the catalytic pathway, namely the effects ofprotein conformational flexibility on the enzyme-complex geometries andthe activation and reaction energies.

(v) Generation of the Full Reaction Free Energy Surfaces for theGas-Addition Reactions

A complete statistical ensemble (conformational average) of enzymestates over the complete course of a reaction step may be generated fromsemi-empirical QM/MM MD simulations for a grid of points defined by thereaction co-ordinates (a free energy hypersurface). A more accuratefree-energy surface may then generated at ab initio QM level by ONIOMQM/MM calculations using multiple configurations, for example up to 120,sampled from the points on the semi-empirical QM/MM reactionhypersurface (Gready et al., 2006; Cummins et al., 2007). These enzymicfree energy surfaces provide reaction and activation free energies thatmay be compared directly with experimental data, such as experimentallymeasured kinetic constants, and also may be used to calculatedifferences in the reaction and activation free energies between wildtype and mutants.

(vi) Definition of Reaction Mechanism and Target Residues

Based on the results of these computations, the inventors were able todeduce a mechanism for the entire sequence of reactions in thecarboxylase catalysis, and to define precise roles for the active-siteresidues, singly and in concert (Kannappan and Gready, 2008). From theQM fragment calculations, a pair of key amino acid residues wereidentified, one acting as a base and the other acting as an acid, foreach reaction step. In particular, the pair HIS294 and LYS334 wereidentified for the gas-addition step.

For the Rubisco carboxylase reaction, the starting point is the Rubiscocomplex with the enediolate form of RuBP bound to the active site andthe CO₂ molecule held at a van der Waals interaction distance to the C2carbon of the enediolate. This state is represented as I in FIGS. 1, 3and 4. The reaction proceeds through a transition state characterized bythe formation of a partial covalent bond between the carbon atom of CO₂and the C2 carbon of the enediolate, accompanied by partial double bondsbetween the C2 and C3 carbon atoms and between the C3 and O3 atoms ofthe enediolate. This state is represented as II in FIGS. 3 and 4. Thereaction step ends with the complete formation of a covalent bondbetween the gas molecule and the C2 carbon of the β-keto intermediate(2C3KABP). This state is represented as III in FIGS. 1, 3 and 4.

In the gas-addition step, HIS294 acts as a base to remove a protoncompletely from the O3 atom; this transfers a partial negative charge tothe C2 carbon and enables it to form a covalent bond with the carbonatom of CO₂, and also transfers the negative charge to the nascentcarboxylate group. LYS334, which is positively charged, helps instabilizing this negative charge developing on the nascent carboxylategroup. These features can be seen in the detailed structures for I-IIIin FIG. 3. Hence, the basicity of HIS294 and the acidity (charge) ofLYS334 are crucial to the gas-addition step.

Modifying the properties of these two residues, for example, bysterically altering the orientation/distance of their interactions withthe enediolate substrate or β-keto intermediate or electronicallyaltering the charge on the atoms interacting with the enediolatesubstrate or β-keto intermediate may affect the energetics of thegas-addition step. HIS294 and LYS334 are, thus, identified as “TargetResidues”, broadly defined to be residues predicted to have asignificant effect on the reaction mechanism and energetics. HIS294 andLYS334 are in the C-terminal domain, are spatially separated, and affectdifferent parts of the enediolate substrate or β-keto intermediate.Hence, the amino acids which may affect their properties have beenclassified into different regions; Region 2 for His294 and Region 3 forLys334, as shown in FIG. 19.

Although residue ASN123 was not included in the FM20 active-sitefragment model for the QM calculations, examination of crystalstructures and the preliminary QM/QM calculations suggested that it alsois involved in stabilizing the charge on the nascent carboxylate groupadded at C2. Furthermore, examination of crystal structures showedresidues E60 and Y20 are positioned to directly alter the charge onLYS334 (i.e. the charge/orientation of LYS334 can be altered bymanipulating E60 and Y20), and the C2-carboxylate group of theintermediate, 2C3KABP. Thus, E60, Y20 and N123 were also identified asTarget Residues. These three residues are in the N-terminal domain ofthe LSU and, thus, amino acids which may affect their properties wereclassified as belonging to a different region (Region 1) from those ofHIS294 and LYS334 (FIG. 19). These three residues are strictly conservedin all catalytically active Rubisco LSUs and predicted to act in aconcerted manner in the gas-addition step. This may be gauged byinspection of FIGS. 8, 9, 10, 12 and 15, which provide different viewsof the relative disposition of ASN123, GLU60 and Tyr20 with respect tothe carboxylate group of the β-keto intermediate analogue (2C3KABP).These figures show that ASN123, GLU60 and Tyr20 are attached to threeseparate secondary structure regions of the N-terminal domain and thattheir sidechains extend into the active site in a tripartiteconstellation.

In summary, the above method comprises a full suite of computationalmethods for investigating mechanistic, energetic and stability issues atglobal or more detailed levels for the carboxylation and oxygenationsteps for wild type and any predicted Candidate Mutant of Rubisco. Inthis manner, it was possible to identify one or more Target Residues toact as the focus for the phylogenetic grafting.

Protein Comparisons—Phylogenetic Grafting

In its broadest form, the method described herein also comprises thecomparison of at least one second protein with at least the firstprotein. The second protein may originate from the same or a differentphylogenetic branch as the first protein. The process of comparisonentails the identification of at least one Variant amino acid Residuebetween the first protein and the second protein. A plurality of VariantResidues of the second protein act as a pool of different specific aminoacid residue identities which may be “grafted” onto the first protein inan attempt to improve the functional property of the first proteinmediated by the Target Residues.

Taking Rubisco as an example, phylogenetic branch-specific changes inthe Rubisco amino acid sequence, such as changes in Rubiscos fromphylogenetic groups of different evolutionary lineages or in Rubiscoswhich express environment-specific changes, represent possible partialoptimizations of the Rubiscos' catalytic efficiency. A strategy, termed“phylogenetic grafting”, was developed to identify the key residueswhich represent these partial evolutionary solutions and to selectively“transplant” these residues into a host Rubisco, such as a Rubisco fromSynechococcus sp., by changing the specific host residues to those ofthe donor Rubisco or donor group of Rubiscos with one or more improved(or preferred) kinetic features, with a view to producing a host Rubiscowith these improved kinetic features.

Partial evolutionary solutions described above were identified by aprocedure of combining the results of the computational studies (theTarget Residues), as shown in Flowchart 1, left hand column, with thoseof the phylogenetic analysis (the Variant Residues), as shown inFlowchart 1, right hand column, to select the Candidate Residues, asshown in Flowchart 1, middle column. These solutions are distributedamongst the Candidate Residues in characteristic (consensus) conservedsequence changes of the LSU among different phylogenetic branches ofRubiscos, or in changes among Rubiscos from the same branch which arebetter adapted to specific environments, e.g. dry/wet or hot/cold.

The integration of the results of the computational studies with thoseof the phylogenetic analysis to identify a specific subset of VariantResidues (i.e. the Candidate Residues) allows differentiation betweenresidues which may affect a functional property, for example, theefficiency of the gas-addition step, from other characteristic(consensus) conserved sequence changes between phylogenetic branches,which may represent, for example, neutral phylogenetic drift or abranch-specific physiological role. Taking the example of a Rubiscoenzyme, a branch-specific physiological role may include folding andassembly of the protein, including interactions with the small subunit,or protein stability.

(i) Identification of Variant Residues by Phylogenetic Analyses

The combined use of the computationally-deduced mechanisms to identifyTarget Residues with sequence conservation and phylogenetic informationin order to identify the Variant Residues is illustrated by thefollowing discussion of specificity factors of Rubisco. The very highspecificity factors of red-algal Rubiscos may be attributed to residueswhich are in common between cyanobacterial and flowering plant Rubiscos,but differ in red-algal Rubiscos. Such residues are defined herein as“Variant Residues”. If single Variant Residues or a plurality of VariantResidues which act as specificity-determining factors in red-algalRubiscos are identified and selectively incorporated into floweringplant/cyanobacterial Rubiscos, then a Rubisco which is physiologicallyactive in the host organism may be produced which has higher specificityfor CO₂ than the native enzyme.

First-shell residues, i.e. those residues directly coordinating to thereaction centre (Glu60, Asn123, Lys175, LYS177, KCX201, Asp203, Glu204,His294 and Lys334) are totally conserved among Rubiscos. Thisconservation is illustrated in FIG. 5, which shows an alignment ofRubisco LSU sequences from photosynthetic organisms belonging tothirteen different phyla covering red algae, cyanobacteria, glaucophytaand plants (10 phyla). Where more than one Rubisco sequence wasavailable in a phylum, a 50% consensus sequence was used to representthat phylum. The consensus sequences were obtained using the server athttp://coot.embl.de/Alignment//consensus.html. FIG. 5 also shows thatthe Rubisco LSU sequence of 475 residues (plants and cyanobacteria) isin general highly conserved, including the almost complete absence ofgaps except for minor differences at the N- and C-termini.

However, residues in the second and subsequent shells surrounding thereaction centre show variation among the main Rubisco branches offlowering plants, red algae and cyanobacteria. Red algae show thegreatest specificity for CO₂, as identified by the CO₂/O₂ ratio of ˜160compared with ˜80 for green plants and ˜40 for cyanobacteria. Thesequence variation among flowering plants, red algae and cyanobacteriais more clearly illustrated in the alignment in FIG. 6 which comprisesonly the 50% consensus sequences of Rubisco LSUs from red algae(rhodophyta; 9 species), cyanobacteria (11 species) and flowering plants(magnoliophyta; 134 species), already shown in FIG. 5. FIG. 6 shows thatthere are 134 residues that are the same in flowering plants andcyanobacteria but different in red algae, i.e. the Variant Residues. Thedatabase accession numbers for each of the sequences used in thealignments in FIGS. 5 and 6 are given in Table 1, together with the SEQID NOS for the computer-readable sequence listings.

In this example, 134 Variant Residues were identified from the RubiscoLSU, amongst which are distributed the residues which are responsiblefor the partial evolutionary solution for increased specificity which isexhibited by red algal Rubiscos. These are shown as grey-shaded residuesin the alignment in FIG. 6. As the specificity-determining factors maybe encoded by combinations of several Variant Residues, many thousandsof such combinations are possible. Hence, in order to be of anypractical use, the subset which comprises the specificity determinantsneeds to be selected from the list of Variant Residues.

(ii)(a) Identification of Candidate Residues

Using methods described below, specific Variant Residues were identifiedwhich have the potential to affect the gas-addition step of the reactioncatalysed by Rubisco, and these were termed “Candidate Residues”. Thisallowed conserved changes between phylogenetic branches orsub-branches/sub-species, which may represent neutral phylogenetic driftor which may have a branch-specific physiological role, such as in thestability, folding or assembly of the Rubsico LSU, to be disregarded.

Many of the Variant Residues may not contribute to the improved propertyof the Rubisco and consequently may not be part of the evolutionarysolution for, in this example, increased CO₂ specificity, but rather aresilent mutations or mutations relevant to other enzyme properties, suchas the folding and assembly of the protein, or its stability, in thecell. In order to identify the Variant Residues most likely to be partof the evolutionary solution for the improved property, in this exampleincreased CO₂ specificity, the mechanistic insights obtained from the QMcalculations were employed to select Candidate Residues from theplurality of Variant Residues. This procedure was based on thehypothesis that Variant Residues which can influence the functionalityof the Target Residues identified by the computational chemistry step asinvolved in the gas-addition step in Rubisco, form a part of theevolutionary solution. This was the primary criterion used to selectfrom the Variant Residues to obtain a subset of residues here called“Candidate Residues”.

In general, the selection process was based on assessing the spatialproximity of the Variant Residues to the Target Residues and estimatingand ranking their ability to influence the electrostatics andorientation of the Target Residues. Selection may utilise visualscreening of crystallographic structures using a molecular modelling andvisualization program package such as Accelrys Discovery Studio v2.0(Accelrys Software Inc., San Diego, Calif., 2007), although othersimilar modelling packages could be used. Standard chemical concepts forintermolecular interactions, such as charge-charge electrostaticpairing, typical van der Waals and hydrogen-bonding distances, andspace-filling models for amino acid sidechains may be used in an initialscan of residues for selection. The procedure may also be systematized,for example, by mapping all the atom-to-atom electrostatic andhydrophobic interactions of each of the Variant Residues with all otheramino acid residues that are within 3-5 Å in distance and excludingthose interactions which are equivalent in the sequences of the firstand second protein.

Examples of such equivalent interactions include backbone-backboneinteractions which are generally, but not always, unaltered by mutation.Interactions were also considered equivalent, for example, if ahydrophobic interaction in the sequence of one protein involved an α orβ aliphatic carbon of the side chain of a Variant Residue with an atomof a non-Variant Residue, and in the sequence of the second protein theamino acid Variant Residue, while different from that in the sequence ofthe other protein, also had an α or β aliphatic carbon in the side chaininteracting with the same non-Variant Residue as in the first proteinsequence.

Interactions of methyl groups in the amino acid side chains, such asthose in valine, leucine and isoleucine were considered equivalent ifonly the particular methyl group was involved in the interaction with anon-Variant Residue. Hydrogen bonds formed by the carboxylate groups ofaspartate and glutamate residues were also considered equivalent if thecorresponding hydrogen-bonding distances were similar.

After screening the Variant Residues for differences in interactionpatterns between the sequences of the first and second protein, onlythose Variant Residues which had the potential to affect an identifiedTarget Residue through changed interaction patterns were retained. Thepotential of a Variant Residue to affect a Target Residue was recognizedby the interaction of a Variant Residue with the Target Residue or withamino acid residues adjacent to Target Residues or with amino acidresidues in the secondary structural unit harbouring the Target Residue.Even Variant Residues that are parts of loops, turns or unstructuredstrands, but which are connected to the secondary structural unitsharbouring the Target Residue, have the potential to alter theorientation of a Target Residue by assisting in repositioning of thesecondary structural units through changed interactions. The selectedVariant Residues, which had one or more variant interactions and thepotential to influence Target Residues constituted the set of “CandidateResidues”. The 20 Candidate Residues identified as able to influence theTarget Residues in Region 1, i.e. ASN123, Glu60 and TYR20, areidentified by reverse shading in the alignment in FIG. 7, and are showngraphically in FIG. 13. They are also listed in Table 2.

(ii)(b) Identification of Alternative Candidate Residues and DivergentCandidate Residues (ACRs and DVRs)

The above-described scheme for the selection of a Candidate Residuerelies on a selection criterion that the Candidate Residue is present ina consensus sequence of a second protein exhibiting an improved ordesirable property, while being different from the corresponding residuein a plurality of consensus sequences of first proteins not exhibitingthe improved or desirable property, and where the consensus sequences ofthe first proteins share the same residue. Thus, using the example ofCO₂ specificity in Rubisco, the Candidate Residue will be a residuewhich is present in the red algae consensus sequence, and which isdifferent from the residue common to both the consensus sequences offlowering plants and cyanobacteria.

Other partial evolutionary solutions may also be expressed in residuesfound in the pool of Variant Residues. These have been termedAlternative Candidate Residues and Divergent Candidate Residues. Thesepartial solutions found in nature may be used to extend the process ofselecting Candidate Mutants, to produce an expanded pool of alternativeor supplementary residues with which to influence Target Residues.

For example, where the selected residue of the second protein is not themajority residue found in the consensus sequence of the second proteinbut instead is found at lower frequency in a plurality of the secondproteins, while still different from the residues present in a pluralityof consensus sequences of first proteins, and where the consensussequences of the first proteins share the same residue, the residue istermed an Alternative Candidate Residue (ACR). The ACR represents analternative to the consensus residue at a Candidate Residue position. Asfor a Candidate Residue, an ACR must still satisfy the selectioncriteria related to influencing a relevant Target Residue. A purpose forintroducing ACRs may be to provide residues for grafting which aresuspected to be associated with a greater improvement of the desirableproperty than the majority residue of the consensus sequence of thesecond protein.

Thus, using the example of CO₂ specificity in Rubisco, the AlternativeCandidate Residue will be a residue which is expressed by at least oneof the red algae which contribute to the red algae consensus sequencebut which is not the majority residue which is contained in theconsensus sequence, and which is different to the residue common to boththe consensus sequences of green plants and cyanobacteria The red algalspecies Griffithsia monolis has a higher catalytic rate compared withother red algal species while maintaining the high specificity typicalof red algae (Whitney et al., 2001), and hence the Griffithsia monolissequence may be used as a source of ACRs. The variation of the RubiscoN-terminal domain sequence between G. monolis and that of the red algaeconsensus sequence and a typical (reference) red algal species, Galdieripartita, is illustrated in FIG. 14. This shows ACRs at residues 36, 51,54, 88 and 104. Note that residue 36 is also a DCR.

A Co-variant Residue (CvR) may be identified in the sequence of a secondprotein from a particular species, as being in the vicinity of anAlternative Candidate Residue (ACR) and showing complementary variationto the ACR. This variation at the position of the CvR, which is notpresent in the consensus sequence for the second protein, may besuspected to reflect complementary changes in the structural and/orelectrostatic properties of the ACR and CvR. These complementary changesmay constitute a partial evolutionary solution. Identification of CvRsprovides a means to identify auxiliary residue positions which may bemutated in the first protein to better accommodate changes made fromtransplanting ACRs.

Yet another partial evolutionary solution may also be expressed inresidues found in the pool of Variant Residues where residues from atleast three phylogenetic branches are examined and the selected residueis predicted to influence at least one Target Residue and is found inthe consensus sequence of the second protein from one branch while beingdifferent from the residues present in the consensus sequences of atleast two other branches, and where the consensus sequences of the firstproteins are also different at the same position. Such a residue istermed a Divergent Candidate Residue (DCR). As for a Candidate Residue,a DCR must still satisfy the selection criteria related to influencing arelevant Target Residue. A purpose for introducing a DCR may be toprovide residues for grafting which are suspected of being associatedwith the improved or desirable property, but which may also be expectedto produce a greater variation of the expressed properties whensubstituted into different first (host) proteins from the at least twophylogenetic branches than would be expected if the substitution waswith a Candidate Residue.

Thus, using the example of CO₂ specificity in Rubisco, the DivergentCandidate Residue may be a residue which is expressed in the red algaeconsensus sequence, but which is different from the residue expressed inthe consensus sequences of flowering plants and in the consensussequence of cyanobacteria, while at the same time residues of theflowering plant and cyanobacteria consensus sequences also differ atthis position. Six Divergent Candidate Residues identified as able toinfluence the Target Residues in Region 1 (ASN123, Glu60 and TYR20) areidentified by grey shading in the alignment in FIG. 7, and are showngraphically in FIG. 13. Table 2 shows the variation in residue betweenflowering plants and cyanobacteria at these six positions.

TABLE 2 Residue composition table (in percentage) for cyanobacteria,flowering plants and red algae at current 20 Candidate Residues(including three from the C-terminal domain of partner LSU) and 6Divergent Candidate Residue sites. Number of sequences used is shown inbrackets. The DCRs are at the bottom of the table (36, 86, 116, 117,138, 140). Substitution in Cyano- Flowering Red Synechococcus PCC6301 bybacteria plants algae residue in Res (11) (134) (9) red flowering cyano-Sub- No Res % Res % Res % algae plants bacteria region 18 K 73 K 100 I67 K18I K18Q 1A Q 27 — 33 19 D 81 D 92 P 67 D19P D19E D19E 1A E 18 E 8 —33 23 T 100 T 99 G 100 T23G T23N 1A N 1 25 Y 82 Y 98 W 100 Y25W Y25H W18 H 2 51 E 91 E 100 V 56 D51V D51E D 9 I 44 D51I 54 G 55 G 99 S 78 G54AG54R 1C A 45 R 1 A 22 G54S 59 A 100 A 100 G 100 A59G 64 G 100 G 100 A100 G64A 68 T 100 T 99 V 100 T68V 1A A 1 81 K 100 K 100 R 100 K81R 1A 84C 100 C 100 A 89 C84A 1C C 11 87 I 82 I 98 V 100 I87V I87L 1C L 9 L 2 V9 88 E 100 E 100 D 78 E88D 1C E 22 104  P 100 P 100 D 89 P104D 1A E 11P104E 114  T 100 T 100 A 100 T114A 118  T 100 T 100 A 100 T118A 121  V100 V 100 I 100 V121I 1B 271  T 100 T 100 V 100 T271V 297  M 100 M 100 G100 M297G 300  V 100 V 100 T 100 V300T 36 L 73 I 100 V 89 L36V I 18 I 11L36I V 9  86^(†) D 63 H 57 K 89 H86K H86G H86D 1C R 18 G 20 R 11 H86RH86D H86R D 16 116  V 64 M 99 L 100 I116L I116M 1116V 1B M 18 L 1 I 18117  L 100 F 99 T 100 L117T L117F 1B L 1 138  I 82 L 100 M 100 I138MI138L I138L 1B L 18 140  F 82 I 97 L 56 F140L F140V 1B I 18 V 2 I 44F140I F140S S 1 ^(†)For residue 86, only those alternate residues withmore than 5% occurrence are displayed for cyanobacteria and floweringplants.

As shown in Table 2, most CRs have an alternative residue in one or moreof the 3 groups (cyanobacteria, flowering plants, red algae) although inmost cases the consensus residue occurs with >70% frequency. Exceptionsare 59, 64, 81, 114, 118 and 121, and all three CRs (271, 297 and 300)in the C-terminal domain segments of the adjacent LSU (Sub-region 1B).However, the magnitude of this variation is of little significance asthe sequence sets for each group are not phylogenetically balanced.Rather this variation should only be taken as a approximate indicationof degree of conformity with the CR definition. The strongest Mutant #4(T23G/K81R) (see Examples 7 and 11) showed almost no variation.Similarly the strongest mutant of subregion 1B, Mutant #8(V121I/M297G/V300T) (see Example 7), also showed no variation of the3CRs.

(iii) Grouping Candidate Residues, Alternative Candidate Residues andDivergent Candidate Residues into Candidate Mutants

More than one Candidate Residue (CR), Alternative Candidate Residue(ACR) or Divergent Candidate Residue (DCR), or combinations thereof, maycontribute to changes in a single contiguous interaction region betweenthe sequences of the first and second protein. For example, a singlenon-Variant amino acid Residue may interact with two CRs, two ACRs, twoDCRs, or a combination of two residues derived from two of these groups,such that both of the changed interactions may affect the same TargetResidue. The two CRs, two ACRs, two DCRs, or combination may then begrouped into a single Candidate Mutant. Similarly, a given CR, ACR orDCR may contribute to changes in more than one contiguous interactionregion affecting a Target Residue. Thus, there may be other CRs and/orACRs and/or DCRs with which a given CR, ACR or DCR may be grouped toform other Candidate Mutants. These grouped CRs, ACRs, DCRs orcombinations thereof may contribute to a proposed Candidate Mutantenzyme where each grouped CRs, ACRs, DCRs or combination thereof is“grafted” onto the host, replacing the corresponding residues in thesequence of the first (host) protein.

(iv) Combining Candidate Mutants to Produce a Cumulative Effect

If the residue mutations from two or more Candidate Mutants (groups ofone or more CRs and/or ACRs and/or DCRs) affect the same secondarystructural unit harbouring a Target Residue and mutations of each ofthese Candidate Mutants is expected to act in a coordinated fashion inchanging the interaction, then the Candidate Mutants can be furthercombined to form a single combined Candidate Mutant. For example, if aTarget Residue is part of a helix with one Candidate Mutant interactingwith the N-terminal end of the helix and another Candidate Mutantinteracting with the C-terminal end of the helix, with both interactionsinvolving addition of a strong hydrophobic interaction in going from thesequence of the first protein to the sequence of the second protein,then a combined Candidate Mutant with both the Candidate Mutants graftedinto the sequence of the first protein would be predicted to showconcerted effects in repositioning the helix.

(v) Ranking Mutants

Despite the large reduction in the number of residues for considerationfor mutation that may be effected by the initial selection of theVariant Residues against Target Residues to produce the list ofCandidate Residues (CRs), and, optionally, Alternative CandidateResidues (ACRs) and Divergent Candidate Residues (DCRs), the number ofpredicted Candidate Mutants that could result from grouping the CRs,ACRs and DCRs could still be large. Consequently, it is useful to rankthe Candidate Mutants based on their predicted potential to showenhancement of the desired functional property. The higher rankedCandidate Mutants may then be the first choice for further computationaland experimental assessments, thus minimizing effort and cost. Asillustrated in Flowchart 2, several principles may be considered in theranking;

-   (a) The Target Residue(s) affected by the Candidate Mutant.    Different Target Residues may have different levels of participation    in the reaction step, and, hence, relative importance. For example,    one Target Residue may be directly involved in a proton transfer,    while another may just be a passive hydrogen-bond donor/acceptor.    For a Target Residue with greater participation in the reaction    step, the effect of mutation of a related Candidate Mutant is    predicted to be greater, and, hence, the corresponding Candidate    Mutant is ranked higher.-   (b) Level of interaction of the CRs and/or ACRs and/or DCRs in the    Candidate Mutant. If the predicted change in interactions associated    with mutations for a Candidate Mutant involves formation, or    elimination, of a strong electrostatic or hydrophobic interaction,    then the ranking will be higher.-   (c) Number of interaction changes accompanying mutations for a    Candidate Mutant. Even if the mutations involve addition, or    removal, of only weak interactions, the total changes may involve    many such interactions within the Target-Residue protein    environment, leading to a large net cumulative effect on the    structure and electrostatics, and, hence, produce a pronounced    effect on the functional property. Hence, such mutations may be    ranked highly.

(vi) Extended Phylogenetic Grafting Predictions

Extended phylogenetic grafting predictions may be used to exploit thecapacity of the phylogenetic grafting procedure to “learn fromexperience” through interpretation of the results (successes andfailures) from cycles of application of the core method of predictionand testing of Candidate Mutants for proteins of interest describedabove. While the core method described above focusses on recognizingCandidate Residues, Alternative Candidate Residues and DivergentCandidate Residues and grouping them into Candidate Mutants based onnetworks of interactions of these residues, the initial results forRubisco detailed in Example 3 showed that a proportion of theseCandidate Mutants were ineffective or even slightly deleterious to theRubisco function, although not greatly. The extended phylogeneticgrafting strategy allowed this accumulated knowledge, both successes andfailures, to be re-interpreted and built into a method furthercustomized for the particular protein application, and that may continueto be refined as additional results are obtained. The interactionbetween the extended phylogenetic grafting technology and the coremethod described above is shown in Flowcharts 1 to 3.

The extended phylogenetic grafting strategy has three main components.Firstly, refinement of the concept of interacting networks of CandidateResidues, and/or Alternative Candidate Residues and/or DivergentCandidate Residues as the basis of the core method for grouping intoCandidate Mutants. Examination of the initial successes and failures ofRegion 1 mutants of Rubisco, and in particular comparing SynechococcusMutant #6a and its component Mutants #4 and #1a (discussed further inExamples 3 and 4), suggested that an improved framework for predictionwould involve recognising that there are “hotspots” for evolutionaryadaptation which contain the partial evolutionary solutions to improvedRubisco, and that identification of these “mutatable subregions”provides a better, or supplementary, basis for identifying CandidateResidues, Alternative Candidate Residues and Divergent CandidateResidues which should be preferentially grouped to form CandidateMutants in order to manipulate Rubisco's functional properties, ratherthan using solely the interaction networks within the Regions, as in thecore method. Thus, in the extended method, the focus of investigationwas more on identifying spatial regions than on identifying interactingnetworks of residues.

Secondly, re-interpretation of the initial results for Region 1 mutantsof Rubisco within this framework allowed identification of spatiallycontiguous volumes of protein structure, called Sub-regions, containinga subset of the Region's CRs (including initially identified ACRs andDCRs), and, which could be predicted to preferentially influence theproperties of a particular Target Residue or Target Residues linked tothe Region. Identification of these subsets of the Region's CRs, ACRsand DCRs provides a means by which they may be preferentially grouped toform Candidate Mutants.

Thirdly, identification of Sub-regions with imprecise and overlappingboundaries provides a basis for identifying additional CRs, ACRs, CvRsand DCRs which are predicted to interact with the core subsets of CRs,ACRs and DCRs and which may be recruited to the core subsets to provideadditional residues for grouping into Candidate Mutants.

Furthermore, identification of Sub-regions as hotspots of naturalsequence variation provides the means to identify and exploit othertypes of sequence diversity data, such as Species-specific VariantResidues (SsVRs) which vary among closely related species, and which mayrepresent partial evolutionary solutions, such as for adaptation toparticular environments such as hot/dry or cold/wet. Using Rubisco as anexample, FIG. 14 illustrates the natural sequence variation among twored algal species and five flowering plant species.

For example, three Sub-regions of Region 1 of the Rubisco LSU wereidentified as mutatable hotspots, and labelled regions 1A, 1B and 1C, asshown in FIGS. 15 and 17. As detailed in Example 4, the inventors haveused the extended method to recruit additional residues to Region 1'sset of preferred residues for mutation and to form additional CandidateMutants predicted to be improvements of the best “lead” mutants producedfrom application of the core method, detailed in Example 3.

In summary, the development of the extended phylogenetic grafting methodprovides a means to improve the functional properties of “lead” mutants.The development of the concept of Sub-regions as evolutionary hotspotsand as a framework for building a database of protein sequence mapped toexperimental data from test of predictions, also positions thephylogenetic grafting technology to better exploit sequence-diversitydata. For example, the aforementioned database may be interrogatedagainst sequence-diversity data to identify residues which may berecruited as species-specific variant residues (SsVRs) for possibleinclusion in Candidate Mutants. For example for Rubisco, sequence dataand, in some cases, kinetic data are available for photosyntheticorganisms growing under varied or atypical environments, including forrelated C3 plant species such as those found in the Balearic Islandswith different tolerances to drought and temperature (Galmés et al.,2005), the drought-adapted southern African Marama bean (Parry et al.,2007), and extremophilic Cyanidiales red algae (Ciniglia et al., 2004).Alternatively for Rubisco, in cases where such sequence diversity andother functional data are available for crop plants such as wheat (Evansand Austin, 1986), the aforementioned database may be used to identifynatural species with improved functional properties that may be used asgermplasm in selective breeding.

Producing Proteins

Proteins with at least one Candidate Residue and/or Alternative Residueand/or Divergent Candidate Residue, and optionally including othersubstitutions of CvRs and/or SsVRs, from the second protein may bemodelled in silico, or may be engineered in vitro and/or in vivo, forexample by site directed mutagenesis of a polynucleotide encoding theprotein and then expressed in an expression system.

Screening Mutant Proteins

Candidate Mutant proteins comprising the combination of Target Residueswith one or more Candidate Residues and/or Alternative CandidateResidues and/or Divergent Candidate Residues, and optionally includingother substitutions of Co-variant Residues (CvRs) and/orSpecies-specific Variant Residues (SsVRs) are thereafter screened toidentify those Candidate Mutant proteins having said improved functionalproperty. The process of screening the Candidate Mutant proteins may useany one or more of several techniques and may comprise catalyticassessment, biochemical assessment, and physiological assessment.

Directed Evolution

The proteins of the invention may be modified by directed evolution.Accordingly, the function of a protein produced by the methods of theinvention may be improved or otherwise modified. In general, directedevolution may involve mutagenizing one or more parental moleculartemplates and identifying any desirable molecules among the progenymolecules. Progeny molecules may then be screened for the desiredproperty, by assessing, for example, the activity of the molecule, thestability of the molecule, and/or frequency of mutation in the molecule.Progeny molecules with desirable properties may then be selected andfurther rounds of mutagenesis and screening performed. Methods by whichdirected evolution may be performed are well known in the art. Exemplarymethods include, among others, rational directed evolution methodsdescribed in U.S. application Ser. No. 10/022,249; and U.S. PublishedApplication No. US-2004-0132977-A1. For a general description ofexperimental methodology and techniques involved in directed evolution,reference may be made to Sambrook et al., Molecular Cloning, ALaboratory Manual 2^(nd) ed., Cold Spring Harbor Laboratory Press, 1989.

In one embodiment of the invention, mutant proteins produced by themethods of the invention may be used as a “starting point” for directedevolution. Taking the example of a Rubisco protein, Candidate Mutantproteins found to have improved enzymatic activity may be selected andfurther optimised by directed evolution. This optimisation mayfacilitate, for example, the relief of steric conflicts by recruitmentof SvRs and other naturally occurring variant residues which may beidentified as complementary to mutations in the Candidate Mutantproteins. Candidate Mutant proteins with improved enzymatic activity maythus serve as a novel starting point for directed evolution as they havedifferent potential for exploring sequence space compared with wild typeRubisco protein. Systems suitable for directed evolution of Rubiscoinclude, but are not limited to those which employ E. coli strain MMI asrecently been reported (Mueller-Cajar et al., 2007).

Rubisco Proteins

The proteins generated in accordance with the invention includefunctional equivalents, variants, active fragments and fusion proteins.For the avoidance of doubt, the following are included within the scopeof the invention: functional equivalents of the active fragments andfusion proteins; active fragments of the functional equivalents andfusion proteins; and fusion proteins comprising a functional equivalentor active fragment.

The term “fragment” refers to a nucleic acid or polypeptide sequencethat encodes a constituent or is a constituent of full-length protein.In terms of the polypeptide, the fragment possesses qualitativebiological activity in common with the full-length protein. Abiologically active fragment of use in accordance with the presentinvention may typically possess at least about 50% of the activity ofthe corresponding full-length protein, more typically at least about 60%of such activity, more typically at least about 70% of such activity,more typically at least about 80% of such activity, more typically atleast about 90% of such activity, and more typically at least about 95%of such activity.

Methods of measuring protein sequence identity are well known in the artand it will be understood by those of skill in the art that in thepresent context, sequence identity is calculated on the basis of aminoacid identity (sometimes referred to as “hard homology”). Sequenceidentity is calculated after aligning the sequences. The inventors haveused the ClustalW (Thompson et al., 1994) program provided within theBioEdit Sequence Alignment Editor (Hall, 1999) to align the sequences.There are several free-to-use and proprietary software packagesavailable that perform sequence alignments and yield effectively thesame results. The identification of Variant Residues may also beperformed by collecting Rubisco sequences, using, for example, BLASTsearches from one or more phylogenetic groups that differ in the kineticproperty selected for improvement, and aligning them against said firstsequence, using, for example, CLUSTALW.

The functional equivalents, active fragments and fusion proteins of theinvention retain the ability of the protein (SEQ ID NO: 23 forSynechococcus sp. PCC7942 and SEQ ID NO: 72 for tobacco) to act as aRubisco enzyme with improved efficiency. Persons skilled the art will,however, be able to devise assays or means for assessing enzymaticactivity.

Functionally-equivalent proteins according to the invention are,therefore, intended to include mutants (such as mutants containing aminoacid substitutions, insertions or deletions). Such mutants may includeproteins in which one or more of the amino acid residues are substitutedwith a conservative or non-conservative amino acid residue and suchsubstituted amino acid residue(s) may or may not be one encoded by thegenetic code.

Particularly preferred are proteins in which several, i.e. 30 and 50,between 20 and 30, between 15 and 20, between 10 and 15, between 5 and10, 1 and 5, 1 and 3, 1 and 2 or just 1 amino acids are substituted,deleted or added in any combination. “Mutant” proteins also includeproteins in which one or more of the amino acid residues include asubstituent group.

Such fragments may be “free-standing”, i.e. not part of or fused toother amino acids or proteins, or they may be comprised within a largerprotein of which they form a part or region. When comprised within alarger protein, the fragment of the invention in one embodiment forms asingle continuous region. Additionally, several fragments may becomprised within a single larger protein.

In one embodiment of the invention there is provided a fusion proteincomprising a protein of the invention fused to a peptide or otherprotein, such as a label, which may be, for instance, bioactive,radioactive, enzymatic or fluorescent, or an antibody.

For example, it is often advantageous to include one or more additionalamino acid sequences which may contain secretory or leader sequences,pro-sequences, sequences which aid in purification, or sequences thatconfer higher protein stability, for example during recombinantproduction. Alternatively or additionally, the mature protein may befused with another compound, such as a compound to increase thehalf-life of the protein (for example, polyethylene glycol).

Enzyme Functions

In another embodiment the protein generated in accordance with theinvention is an enzyme. Where the protein is an enzyme, the function maybe the catalysis of at least one chemical reaction. In other embodimentsthe function may be structural (e.g. serving as a cytoskeletal protein).The function may involve the active or passive transport of a substancewithin the cell or between the cell interior and exterior, or betweendifferent compartments within the cell, or between different regions ofthe organism, for example where the protein is involved in a channel ora membrane pore, or the protein is involved in trafficking of materialsto specific cellular compartments or the protein acts as a chaperone ora transporter. The function may be involved with ligand/receptorinteractions, for example where the protein is a growth factor, acytokine, a neurotransmitter or an intracellular or extracellularligand, or the protein is a receptor for the growth factor, cytokine,neurotransmitter or the intracellular or extracellular ligand.

Where the protein is an enzyme, the enzyme may be involved in catabolismor metabolism. The enzyme may be involved in the synthesis of at leastone product. The enzyme may be involved in the breakdown of at least onesubstrate. The enzyme may be involved in the chemical modification of atleast one substrate, for example the addition or deletion of one or morephosphate groups from a molecule.

The enzymes may suitable for use in, for example, degradation ofpesticides, and detergent residues, for mineral extraction, or for“bulk” or fine chemical processes, such as amylases. The enzymes mayalso be suitable for use in medical applications, and in particular maybe used for minimizing changes to biological and physicochemicalstability.

The enzymes may have specifically engineered properties, for example,the ability to perform optimally in a desired temperature range, anarrower, wider or altered substrate specificity, or the ability toprevent the production and/or release of toxic or potentially toxicbyproducts. The enzyme may be re-designed such that it is an efficientcatalyst for a minor reaction of the wildtype enzyme using either itsnatural substrate or an alternative substrate to produce a differentproduct.

In the context of Rubisco, an improved functional property of Rubiscomay comprise any one or more of improved specificity for CO₂ over O₂(S_(c/o)), improved carboxylation efficiency k^(c) _(cat)/K_(c) ^(air)or improvements in one or both of its component parameters k^(c) _(cat),the carboxylation rate, or K_(c), the affinity for substrate (CO₂), orimprovements in these functional properties over a range oftemperatures, especially at higher temperature. At higher temperaturewildtype Rubisco efficiency is limited by decreased specificity duemostly to a relative increase in the efficiency of the oxygenationreaction compared with that of the carboxylation reaction. ImprovedS_(c/o) over a range of temperatures may be exhibited by a Rubisco ifthe efficiency of the oxygenation reaction does not increase withincreasing temperature to the extent exhibited by a wildtype Rubisco,i.e. there is a decreased rate of increase or no increase in theefficiency of the oxygenation reaction catalyzed by the Rubisco withelevated temperatures, for example as measured between 25° C. and 35°C., when compared with a wild-type Rubisco.

The improved functional property of a Rubisco may be any two of improvedspecificity for CO₂ over O₂ (S_(c/o)), improved carboxylation efficiencyk^(c) _(cat)/K_(c) ^(air) or improvements in one or both of itscomponent parameters k^(c) _(cat), the carboxylation rate, or K_(c), theaffinity for substrate (CO₂), or improvements in these functionalproperties over a range of temperatures, especially at highertemperature. The improved functional property may be any three ofimproved specificity for CO₂ over O₂ (S_(c/o)), improved carboxylationefficiency k^(c) _(cat)/K_(c) ^(air) or improvements in one or both ofits component parameters k^(c) _(cat), the carboxylation rate, or K_(c),the affinity for substrate (CO₂), or improvements in these functionalproperties over a range of temperatures, especially at highertemperature.

The improved functional property of Rubisco, when functionallyincorporated into a plant may result in the generation of a plant withimprovements in any one or more of growth rate, biomass production, leafindex area, Rubisco content (Rubisco mRNA and protein content), carbonto nitrogen ratios of plant leaves, starch content, and photosyntheticperformance. The improvements may be exhibited under optimal growthconditions for the plant. The improvements may be exhibited undersub-optimal growth conditions for the plant, for example but not limitedto under elevated temperatures for growth, or where water, nitrogen orillumination is limiting plant growth, or a combination of any two ormore of the above.

Purification of Rubisco Proteins

The invention provides a method of purifying a Rubisco protein producedaccording to the methods of the invention. The holoenzyme of thefunctional form of Rubisco from eukaryotic organisms (form I Rubisco) isa hexadecamer made of 8 large subunits (LSUs) and 8 small subunits(SSUs), and requires appropriate chaperones to correctly fold andassemble the enzyme correctly. E. coli is the most widely used microbialhost for expressing recombinant DNA and proteins. When the operon codingfor the Rubisco genes (rbcLS and rbcSS) from Synechococcus sp. PCC7942is expressed in E. coli both subunits are abundantly synthesized,however only about 1 to 5% of the expressed LSUs are correctly foldedand assembled into functional form with the amount of functional Rubiscoaccumulating to ˜1 to 3% (wt/wt) of the E. coli soluble protein.

In order to overcome these difficulties, a recently adapted system(Baker et al., 2005, the entire contents of which are incorporatedherein by reference) may be used to purify native or mutant Rubiscoproteins. In this case, the aforementioned system was used for thepurification of Synechococcus sp. PCC7942 Rubisco expressed in E. coli.The first step of the purification method involves fusing into a firstvector the coding sequence for a H₆ tagged ubiquitin (Ub) sequence(H₆Ub) to the 5′ end of an rbcSS gene. A host is then co-transformedwith the first vector and second vector coding for the native (ormutated) large subunit and small subunit of the Rubisco protein, andexpression of the Rubisco protein and vectors is then induced, producingall three Rubisco subunit peptides (i.e. LSU, SSU and H₆UbSSU). Some areassembled into functional Rubisco hexadecamers made up of 8×LSUoctameric cores and different ratios of SSU (at most 8) and H₆UbSSU. TheRubisco protein is purified based on the expression of the H₆ tag fusedto the Rubisco small subunit. This purification may be performed, forexample, using chromatography techniques such as metal affinitychromatography. The Ub fragments may then removed from the Rubiscousing, for example, a Ub-specific protease.

The present invention will now be described with reference to specificexamples, which should not be construed as in any way limiting the scopeof the invention.

EXAMPLES Example 1 Identification of Target Residues ComputationalChemistry

A computational study of the complete Rubisco carboxylation mechanism(Kannappan and Gready, 2008) and complementary oxygenation mechanismusing ab initio QM calculations on an extended active-site fragmentcomplex provides the basis for the strategy.

This fragment complex model comprises fragments of most of theactive-site amino acid residues that have either been established ormooted to have a key role in the series of reactions that are catalyzedat the Rubisco active site. It contains all residues directlycoordinated to Mg²⁺ or interacting with the reactive centre of thesubstrate. This fragment complex model was built from the coordinates ofthe crystal structure with PDB code 8ruc (crystal structure of thecomplex of activated Rubisco with Mg²⁺ and 2-carboxyarabinitol1,5-bisphosphate (2CABP)). Initially, the fragment complex model ofRubisco with 2-carboxy-3-ketorarabinitol 1,5-bisphosphate (2C3KABP), astructural analogue of 2CABP and the actual reaction intermediateproduced during the Rubisco carboxylase activity, was built from thecrystallographic coordinates. As shown in FIG. 2, the 77-atom fragmentmodel, named FM20, comprises molecular-fragment species to represent theLYS175, LYS177, ASP203, GLU204, KCX201 (carbamylated LYS201), HIS294,and LYS334 amino acid residues and the 4-carbon fragment of theenediolate form of the substrate RuBP, plus the water and carbon dioxidemolecules. This structure was optimized using the quantum chemistrypackage Gaussian 03 (Frisch et al., 2004). Guess geometries for all theother reaction species on the carboxylase reaction pathway (shown inFIGS. 1 and 3) were generated by modifying this optimized geometry, andtheir optimum energy structures were then obtained, also using theGaussian 03 package. In general, several possible structures for eachspecies differing, for example, by H-bonding pattern or orientation ofatoms, were considered. Consequently the roles of these groups in thegas-addition and subsequent steps of the carboxylase and oxygenasereactions were examined leading to more confident predictions, inparticular, for definition of the groups involved directly in thegas-addition (CO₂ or O₂) steps and the relative energetics of the twosteps.

The analysis is focused entirely on the large subunit (LSU). Althoughmost Rubiscos, including green plants, algae and cyanobacteria, arecomplex multimeric (hexadecameric) proteins consisting of 8 largesubunits (LSU; ˜475 residues) and 8 small subunits (SSU; ˜140 residues),the active-site chemistry is conducted by a protein region consisting ofa dimer of LSUs only, with 8 such dimer active sites in thehexadecameric protein. A moiety of the C-terminal (TIM-barrel) domain ofone LSU contains most of the active-site residues while a smaller regionof the N-terminal domain of the adjacent LSU completes the active site.However, predictions arising more generally from bioinformatics studiessuggest other regions may be involved in modulating the chemistry, e.g.,intersubunit contacts (LSU-LSU or LSU-SSU).

FIG. 1 shows a schematic of the proposed carboxylase reaction mechanismbased on the QM calculations. The curved arrows indicate the flow ofelectrons, signifying the bond-formation and bond-breaking events, whichlead to the successive reaction species. The schematic defines theparticipation of amino acid residues in each reaction step, and thegas-addition step (carboxylation), in particular. The residues predictedto have a role in the gas-addition step comprise the set of TargetResidues defined previously. FIGS. 3 and 4 provide geometries andrelative energies, respectively, of the carboxylase reaction species.

The most significant features of the proposed reaction mechanism arediscussed hereafter.

Firstly the inventors have made the surprising discovery that H₂O[Mg] isnot displaced from Mg-coordination by CO₂ during carboxylation. Thewater molecule in fact assists in binding CO₂ to the active site andcontributes to the stability of the carboxylated product and thecorresponding TS. The same water molecule acts as the water of hydrationin the later step. Previously this role of hydration had been assignedto a water molecule found in the vicinity of the coordination sphere.

The inventors have made the further surprising discovery that the O₂atom remains unprotonated in the enediolate intermediate, despiteexpectations from general chemical principles that it would need to bedeprotonated in order to direct carboxylation exclusively to C2, ratherthan to C3. ESP-derived atomic charges also show that O3 is morenegative than O2. However, this unexpected result is explained by theobservation of strong hydrogen bonds between LYS175 and protonatedKCX201 with O2, which effectively prevent O2 from directingcarboxylation to C3. Additionally, as LYS334 is H-bonded to theP1-phosphate group in the enzyme, its interaction with the substrate CO₂would be disrupted if C3 carboxylation were to take place, leaving noscope for stabilization of the corresponding TS and intermediate.

Further features of the reaction mechanism elucidated by the inventorsare as follows. KCX201 has a direct role only in the initial enolizationreaction and it remains in a protonated state after enolization. KCX201and LYS175 have a role in hindering C3-carboxylation by partiallyneutralizing the negative charge on O2. HIS294 has a significant role inthe multi-step catalysis of Rubisco. It shuttles the proton betweenN_(ε) and O3, modulating the C3-O3 bond length appropriately. GLU204activates the Mg-coordinated water molecule for hydration by abstractingits proton. Thus, both carboxylation and hydration take place on thesame face of the enediolate intermediate. The H3 proton is eventuallytransferred to O2 only after the formation of the aci-acid intermediate(VII). The charge on the aci-acid intermediate is stabilized by LYS175and LYS334. LYS175 ensures stereospecific protonation of the C2-carbonto yield the final products. LYS334 shares its proton with LYS175.

On the basis of the above findings, the inventors have identified twoamino acid residues, one acting as a base the other as an acid, for eachreaction step. For the gas-addition step, HIS294 acts as a base byabstracting the proton from O3, while LYS334 is the acid donating aproton to stabilize the carboxylate group formed by addition of CO₂.Alteration in the steric or electronic environment of these two keyresidues, or any other residues that are structurally or chemically(through electrostatic interactions) linked to them, would impact thespecificity of the enzyme and likely also affect k_(cat).

Residues TYR20GLU60, ASN123 were also identified as being crucial forappropriate orientation of gas molecules relative to the substrate priorto addition, and for the stability of the gas-adduct and thecorresponding transition state structures. These five residues comprisean initial group of Target Residues for further examination.

At this stage in the summary of the solution of the problem of reductionof sequence space for Rubisco illustrated in Flowchart 4, step 2 isachieved.

Example 2 Phylogenetic Analysis to Identify Variant Residues ContainingSpecificity-Determining Residues

Rubisco LSU sequences from available phyla of photosynthetic organismswere collected for phylogenetic analysis from publicly availabledatabases at NCBI (www.ncbi.nlm.nih.gov/) and JGI(http://img.jgi.doe.gov/cgi-bin/pub/main.cgi) by performing proteinBLAST searches (Altschul et al., 1997) using the spinach Rubisco LSUsequence as the query sequence. As the LSU sequences are so distinctive,and the conservation relatively high compared with mostprotein-homologue classes over such wide evolutionary distances, theyare easy to identify and other free-to-use or proprietary searchsoftware would work equally well.

Alignment of the extracted Rubisco LSU sequences from photosyntheticorganisms belonging to thirteen different phyla covering red algae,cyanobacteria, glaucophyta and plants (10 phyla) was carried out usingClustalW software (Thompson et al., 1994) within the BioEdit SequenceAlignment Editor (Hall, 1999) to assess their diversity. An alignment isshown in FIG. 5; in cases where there is more than one sequence from asingle phylum, a 50% consensus sequence has been used for efficiency.The consensus sequences were obtained using the server athttp://coot.embl.de/Alignment//consensus.html. Any other proprietary orfree-to-use alignment tool could be used for the same purpose due to thefact that the overall conservation of these Rubiscos is so high thateffectively the same alignment results would be obtained.

FIG. 5 shows how diverse the Rubisco LSU sequences from distantphylogenies can be. Thus, although information on partial evolutionarysolutions for adaptation of Rubiscos to specific environments isembedded in this diversity, it is impossible to analyze this informationdirectly to identify residues responsible for specific adaptations, suchas increased specificity.

To solve this problem, the inventors have developed the hypothesis-basedphylogenetic grafting method and applied it to identification of Rubiscoresidues which already represent natural partial evolutionary solutionsfor enhanced specificity (S_(C/O)). It is well known that diversephotosynthetic organisms exhibit characteristically different values forS_(C/O). The majority of land plants possess a typical S_(C/O) value of80, while red algae are known to have the highest specificity factor(˜160). The specificity factor for cyanobacteria has a modest value ofabout 40.

As cyanobacteria are a common ancestor to both land plants and redalgae, and as land plants diverged from cyanobacteria earlier inevolution compared with red algae(http://www.geocities.con/we_evolve/Plants/chloroplast.html) the partialevolutionary solution for enhanced specificity embedded in amino acidresidue changes in red algae can be partially revealed by comparison ofRubisco LSU sequences from these three groups. FIG. 6 shows thealignment of 50% consensus sequences of Rubisco LSUs from red algae,cyanobacteria and flowering (green) plants previously shown in FIG. 5,but now shown with grey shading to highlight the 134 residues in redalgae which differ from those in common in cyanobacteria and floweringplants, i.e. the Variant Residues. As there is a general agreement thatsingle-residue changes will not result in substantial improvement inRubisco specificity (otherwise evolution would have been able to exploresequence space reasonably easily to optimize specificity in givenorganisms), the number of multiple mutations, for example of 2-10residues, which would need to be tested to explore even the reducedsequence space of these 134 residues to identify thespecificity-determining residues is impossibly large. In making use ofthis list of Variant Residues, variations that are not relevant to theenzyme property of interest are filtered (i.e. specificity). The problemof sequenced space to be solved is illustrated in Flowchart 4.

At this stage in the summary of the solution of the problem of reductionof sequence space for Rubisco illustrated in Flowchart 4, step 3 isachieved.

Example 3 Identification, Grouping and Ranking of Candidate Residues,and Prediction of Candidate Mutants Using Core Phylogenetic GraftingMethod

In order to identify the specificity-determining residues that accountfor the increased specificity of red algal Rubiscos, the inventors usedthe enzyme-mechanistic insights from the QM calculations described inExample 1 to develop a procedure for selecting a subset of the 134Variant Residues identified in Example 2. The Variant Residues,identified in Example 2, were selected against the Target Residues,identified in Example 1 to have a functional role in the gas-additionstep, in order to identify Candidate Residues. Several of the selectedCandidate Residues were also Alternative Candidate Residues. Inaddition, several Divergent Candidate Residues were also selected. Thisused a procedure based on the general principle that evolutionarychanges of residues which modified the properties of these TargetResidues would alter their specificity and kinetic efficiency. Thus, anyVariant Residue that has the potential to affect the Target Residueselectronically or structurally, and, hence, cause a change in thefunctional property of the enzyme, in this case specificity and kineticefficiency, is deemed to be part of the partial evolutionary solution tooptimisation of the property.

The selection procedure was applied to identify such Candidate Residues,Alternative Candidate Residues and Divergent Candidate Residues.Selection was carried out by visual analysis and comparison ofdifferences in inter-residue interactions with Accelrys Discovery Studiov1.5.1 (Accelrys Software Inc., San Diego, Calif., 2005), using thecrystal structures of Rubiscos from spinach (PDB code: 8ruc) andGaldieria partita (PDB code: 1BWV). The crystal structure of spinachRubisco was used instead of Rubisco from Synechococcus sp. PCC6301 (PDBcode: 1RB1) because the resolution of the available structures issuperior for the spinach Rubisco structure. However, the inventorsaccounted for residue changes between LSUs of spinach and Synechococcussp. PCC6301 Rubiscos when analyzing the inter-residue interactions, andused the Synechococcus structure also for reference.

Three of the five Target Residues, TYR20, GLU60 and ASN123 are in theN-terminal domain of the Rubisco LSU, while HIS294 and LYS334 are in theC-terminal domain that forms the TIM-barrel structure (FIG. 8). For thepurpose of classifying groups of CRs, ACRs and DCRs that can formsubsets of residues of the partial evolutionary solutions, the TargetResidues were classified as belonging to three different Regions.Residues TYR20, GLU60 and ASN123 collectively interact with thecarboxylate group of the intermediate formed after CO₂ addition (FIGS.8, 9 and 15). The secondary structural units containing these threeresidues also intertwine with other helices and sheets of the N-terminaldomain (FIGS. 8, 9 and 15). As evident in FIG. 15, ASN123, GLU60 andTYR20 are attached to three separate secondary structure regions of theN-terminal domain and their sidechains extend into the active site in atripartite constellation. Hence, these three Target Residues areclassified as Region 1 residues. HIS294 is in strand P4, which is a partof the TIM barrel; the region surrounding HIS294 is defined as Region 2.Although LYS334 is in the vicinity of HIS294 and Region 1 residues, itis in ‘loop 6’ of the LSU (FIG. 8) and in the open form of the LSU it isseparated from the other Target Residues; hence, the region containingLYS334 is classified as Region 3.

At this stage in the summary of the solution of the problem of reductionof sequence space for Rubisco illustrated in Flowchart 4, steps 4 and 5are achieved.

The initial analysis and Candidate Mutant design is illustrated byconsideration of the Variant Residues in Region 1. As the N-terminaldomain of the LSU of Rubisco is a compact domain (FIGS. 9 and 15),protein-structural considerations suggest that amino acid residuevariations in most of the domain can influence the Target ResiduesTYR20, GLU60 and ASN123. The selection procedure was started by mappingall the electrostatic and hydrophobic interactions between each of theVariant Residues and all other residues in the LSU in both the crystalstructures. Variant Residues that have equivalent interactions in boththe crystal structures were ignored. The equivalent interactions mainlycomprise interactions involving a backbone atom of a Variant Residue,and such interactions occur largely within a helix or between twoβ-strands. The interactions were also considered equivalent if VariantResidues in spinach (or Synechococcus sp. PCC6301) and Galdieria partitadiffer only in the length of the sidechain and the interacting atoms areof the same chemical type and within approximately the same distance inboth the crystal structures. Similarly, interactions involving valine,leucine and isoleucine were considered equivalent if only one methylgroup of the sidechain is involved in the interaction and theinteraction distance does not differ significantly between the twocrystal structures. This process removed some of the Variant Residuesfrom further consideration as potential Candidate Residues (or DivergentCandidate Residues). The remainder of the interactions involving VariantResidues were then analysed for their potential to affect TargetResidues.

A Variant Residue whose sidechain interacts with the backbone orsidechains of Target Residues or with residues that are part of thesecondary structural units harbouring the Target Residues was considereda Candidate Residue (or Divergent Candidate Residue). As an example,Target Residue GLU60 is at the C-terminal end of helix αB and theVariant Residue ILE51, at the N-terminal end of this helix, interactswith another Variant Residue TRP25 in the Galdieria partita LSU (seeFIG. 14 and Table 2), but this interaction is absent in the spinach andSynechococcus sp. PCC6301 LSUs. “Grafting” these Variant Residues fromGaldieria partita into Synechococcus sp. PCC6301 is predicted to have aneffect on the orientation of helix αB and, hence, on GLU60. Both theseVariant Residues 51 and 25 were, thus, considered as Candidate Residues.The positions of these residues in the LSU structure are shown in FIG.9. In this case, it is useful to group these two Candidate Residues thatshare a contiguous interaction region into a single mutation, as it islikely they form a coordinated part of the partial evolutionarysolution. This simplest grouping is numbered Candidate Mutant #1a inTable 3. Such grouped Candidate Residues represent mutations forreplacement of residues (grafting) from the sequence of Galdieriapartita onto the Synechococcus sp. PCC6301 sequence, with the view totransferring features of higher specificity into Synechococcus sp.PCC6301 Rubisco.

Before grafting, the groups of Candidate Residues can be furthercombined into groups that can act further in coordinating and amplifyingthe perturbative effect on a given Target Residue or Target Residues.Such extended grouping is useful if two different groups of CandidateResidues affect the same secondary structural unit. For example, both ofthe Candidate-Residue groups {25, 51} and {54, 84, 87} affect helix αB,which harbours GLU60, through two different interactions. Hence, one ofthe predicted mutants comprised these combined groups (Shown as Mutant#7a in Table 3).

The potential grafted Candidate Mutants were further assessed to checkfor new unfavourable steric interactions introduced by grafting residuesfrom Galdieria partita into Synechococcus sp. PCC6301. Such undesirablesteric interactions may be rectified by adding spatially complementingmutations to the Candidate Mutant, or could be investigated by MDsimulations to assess whether structural relaxation to relieve such badcontacts is energetically accessible.

The final step in the Candidate-Mutant prediction procedure is to rankthe potential grafted mutants to develop a ranked list for use inprioritising experimental testing or detailed computational in silicopre-screening. The ranking reflects the expected degree to which thecombined mutations in the individual Candidate Mutants is expected tochange the functional property, in this example in the direction towardsimprovement of specificity by influencing the chemistry, and relativechemistry, of the gas-addition steps for CO₂ and O₂. Ranking depends ona number of parameters such as the Target Residue affected by theCandidate-Residue group, the strength of the changed interactions of theCandidate-Residue group within the Target-Residue Region, and the numberof such interactions for each Candidate-Residue group.

In addition to the Rubisco sequence from Galdieria partita, the sequenceof another red-algal species Griffithsia monolis, which is known to havea better k^(c) _(cat) than Galdieria partita, was considered in theanalysis. For the initial set of Candidate Residues selected, tworesidues (51 and 54) show differences between G. partita and G. monolis,i.e. they are Alternative Candidate Residues. Candidate Mutants withboth residue variants in positions 51 and 54 were formed, as shown inTable 3 for CM's #1, #5, #6, #7 and #13.

As an example, the set of sixteen Candidate-Residue groups shown inTable 3 was predicted from initial analysis of Region 1 Target Residues,forming 21 potential Candidate Mutants (with G. partita and G. monolisvariants). For each Candidate Mutant, the last column in Table 3 detailsthe predicted structural change associated with the mutations. For someCandidate Mutants, these changes are explained graphically in a figure;the second column of the table gives the figure number for these CMs.Table 3 also shows the rankings of priorities for experimental test.

Table 3 shows that two Divergent Candidate Residues (36, 116 and 140;see Table 2) were selected in this initial analysis for the reasonssummarized for the relevant Candidate Mutants (#9 and #10). Two of theseDCRs (36 and 140) also show differences between G. partita and G.monolis (see Table 2); for Candidate Mutants #9 and #10, the Gm variantof 36 and the Gp variant of 140 were judged to be the most promising fortransplant into Synechococcus.

At this stage in the summary of the solution of the problem of reductionof sequence space for Rubisco illustrated in Flowchart 4, step 6 isachieved.

TABLE 3 Predicted and Ranked Candidate Mutants from Analysis of Region 1in the N-terminal Domain of the Rubisco LSU surrounding Target ResiduesTYR20, GLU60 and ASN123. Superscript Gp and Gm denote the residue fromGaldieria partita and Griffithsia monolis, respectively. No # Fig^(a)Mutant Rank Region Affected  1a  9, 10 Y25W/D51I^(Gp) 3 Adds a newhydrophobic interaction between the C-terminal end of αB and βA. βA isclose to Y20 in sequence.  1b  9, 10 Y25W/D51V^(Gm) 3 Adds a newhydrophobic interaction between the C-terminal end of αB and βA. βA isclose to Y20 in sequence.  2 — A59G/G64A 6 Swapping mutation.Interaction between αB and the long chain that connects αB to βC. Theswapped methyl group is spatially close to Y20 and adjacent to E60.  3 —P49D/D51I 10 Alters the interaction in the short loop connecting αB andβB.  4  9, 10 T23G/K81R 4 Interaction between βA and βC is broken.Affects the positioning of Y20.  5a 10 G54A^(Gp)/C84A/I87V 5 Introducesa strong hydrophobic interaction between αB and βC.  5b 10G54S^(Gm)/C84A/I87V 5 Introduces a strong hydrophobic interactionbetween αB and βC.  6a  9 T23G/Y25W/ 1 Mutant #1a adds a hydrophobicinteraction D51I^(Gp)/K81R between βA and αB, while Mutant #4 breaks theinteraction of βA with βC. These two sets of mutations together may havea large effect on Y20.  6b  9 T23G/Y25W/ 1 Mutant #1b adds a hydrophobicinteraction D51V^(Gm)/K81R between βA and αB, while Mutant #4 breaks theinteraction of βA with βC. These two sets of mutations together may havea large effect on Y20.  7a 10 Y25W/D51I^(Gp)/ 2 Cumulative effect ofMutants #1a and #5a on E60. G54A^(Gp)/C84A/I87V  7b 10 Y25W/D51I^(Gp)/ 2Cumulative effect of Mutants #1a and #5b on E60. G54S^(Gm)/C84A/I87V  7c10 Y25W/D51V^(Gm)/ 2 Cumulative effect of Mutants #1b and #5a on E60.G54A^(Gp)/C84A/I87V  7d 10 Y25W/D51V^(Gm)/ 2 Cumulative effect ofMutants #1b and #5b on E60. G54S^(Gm)/C84A/I87V  8 11 V121I/M297G/ 7Hydrophobic interaction between the two LSUs V300T are broken (residues297 and 300 are from the neighbouring LSU that contains the Mg-complexof the active site being considered). Affects N123.  9 11L36I^(Gm)/I116L/ 8 Forms a large hydrophobic region involving theF140L^(Gp) ends of two adjacent β-strands (βB and βE) and αC. Couldalter the orientation/positioning of N123. 10 11 L36I^(Gm)/I116L/ 3Could together act on α- C and have a cumulative V121I/F140L^(Gp)/effect on N123. M297G/V300T 11 T114A/T118A/ 2 Polar interaction of 114and 118 with 271 in the T271V/V121I partner LSU is broken. 271 forms anew hydrophobic interaction with 121. Impacts N123 12 17 K18I/T23G 5Polar interaction between side-chains of T23 and K18 is broken. ImpactsY20. 13a  9, 10 Y25W/D51I^(Gp)/ 6 (1a + A21) Insertion of A21 moves K21away insert A21 from residue 51 and forms a new hydrophobic interactionwith 151. 14 17 KLTYY-(21-25)- 4 Shape of a coil adjacent to Y20 isaltered, affects AKMGYW orientation of Y20. Involves an insertion (M);see FIG. 6. 15 17 K18I/KLTYY-(21- 1 The change of shape of coil next toY20 is 25)-AKMGYW/ associated with changes to its interaction with 18K81R (loss of polar interaction) and 81 (change in length) and may havea coordinated effect on Y20. 16 — A15S/K18I/T68V/ 9 Possible interactionbetween residues 18 and 68 L407I which could bind N-terminal tail torest of domain,; conserved residue 69 interacts with 407 of partnerLSU,; S15 can form strong H-bonds with backbone carbonyl groups of 408and 409 of partner LSU in red algae. Targets Y20. ^(a)FIGS. 9-11 and 17show the predicted mutation sites.

Example 4 Identification, Grouping and Ranking of Candidate Residues,and Prediction of Candidate Mutants Using Extended Phylogenetic GraftingMethod

As aforementioned and as shown in Flowcharts 1 and 3, the extendedphylogenetic grafting method provides a means to utilise effectivelyknowledge of the “map” of function to mutations, developed fromexperience gained from cycles of application of the core method ofprediction and testing of Candidate Mutants. Use of the extended methodis illustrated in this example with reference to the initial results forpredicted Region 1 Candidate Mutants (Example 3) given in Table 5 anddiscussed in more detail in Example 7.

The extended method was first used to interpret the core-method results.This resulted in identification of a new model for grouping of alreadyidentified CRs, ACRs and DCRs (see CMs in Table 3), which was based onSub-regions as mutatable hotspots rather than focussed on networks ofinteractions as in the core method. The three Sub-regions (1A, 1B and1C) exhibited the property of being predicted to preferentiallyinfluence the properties of one of the three Target Residues linked toRegion 1: Sub-region 1A to TYR20, 1B to ASN123 and 1C to GLU60. This“anchoring” of the three TRs to the Sub-regions of Region 1 is showngraphically in FIG. 15. The Sub-regions are shown graphically in analternative orientation in FIG. 17. The Sub-regions are confinedentirely to the N-terminal domain, except for fragments of theC-terminal domain of the adjacent LSU which form part of Sub-region 1B.

Identification of the Sub-regions provided the basis for identificationof additional CRs and DCRs, using visual inspection and other analysesdescribed previously for identifying CRs and DCRs using the core method,which may be preferentially grouped with CRs and DCRs already identifiedby the core method to form new Candidate Mutants (see Table 4).Additional CRs and DCRs so identified were positions 19, 68, 88 and 104,and 86, 117 and 138, respectively. Alternatively, the identification ofthe Sub-regions provides a new basis for preferential regrouping the CRsand DCRs already identified by the core method to form new CandidateMutants.

The use of the extended method, and the basis for recruiting particularadditional CRs and DCRs, is illustrated below with reference to examplesfor refinement of activity of mutants predicted by the core method andinitially tested (Table 5). The new predicted CMs are shown in Table 4.

TABLE 4 Candidate Mutants predicted using the extended phylogeneticgrafting method to refine the most promising initially predictedCandidate Mutants (Table 3). Also listed are additional single anddouble-residue component mutations of these most promising initiallypredicted Candidate Mutants. No. Fig Mutation Rank Comments 17-1A 17T23G/K18I/T68V/K81R 2 Prediction based on refined 18a-1A 17T23G/K81R/P104E^(Gp) 5 phylogenetic grafting on subregion 18b-1A 17T23G/K81R/P104D^(Gm) 5 1A. 19-1A 17 T23G/D19P/K81R 4 20-1B 16,I116L/L117T/V121I/ 3 Prediction based on refined 17 I138M/F140Lphylogenetic grafting on subregion 1B. Targets residue N123. 21-1A, B 17T23G/K81R/V121I/ 1 Combination of two predicted CMs M297G/V300T thatshowed maximum overall improvement in the enzyme efficiency in kineticassessment study. 22-1A  9, 10 T23G Single-residue components of Mutant#4. 23-1A  9, 10 K81R 24 11 V121I/M297G Double-residue component ofMutant #8. 25 11 M297G Single-residue components of 26-1B 11 V121IMutant #8.

The first example below focuses on the refinement of the best mutant,Mutant #4 (T23G/K81R), from first-round testing, and on subregion 1A. Asshown in Table 3, Mutant #4 is a component with Mutant #1a(Y25W/D51I^(Gp)) of Mutant #6a (T23G/Y25W/D51I^(Gp)/K81R). However,although Mutant #6a showed increased specificity (8.5%, see Table 5), itshowed no efficiency improvement, and overall is inferior to Mutant #4,which showed both increased specificity (10%) and efficiency (8%).Reference to the results for Mutant #1 a indicated it is a relativelypoor mutant with increased specificity of only 3.4% and no change inefficiency. Thus, it was concluded that grouping of the Mutant #4mutations with those of Mutant #1a was ineffective, as the net effectwas not a cumulative improvement but rather the two groups of mutationsapparently interfered disadvantageously. As Sub-region 1A contains theresidue positions of the mutations in Mutant #4, it was deduced thatcoupling of the Mutant #4 mutations with mutations of other CRs and/orDCRs in subregion 1A, may provide a better strategy for furtherimproving on the properties of this “lead” mutant.

Examination of the sequence and structural data by visual and otheranalysis procedures already described, especially an analysis ofspecies-specific covariation data for already identified CRs and DCRs inSub-region 1A, identified three additional CRs, 19, 68 and 104, whichmay influence TR TYR20 or residue 81 (component of #Mutant #4). Hence,the following new CMs, showing the indicated changes in interactions,were predicted as potential improvements on Mutant #4.

In relation to Mutant #17-1A (#4+K18I/T68V), the mutations of K18I andT68V are predicted to result in an altered interaction between theN-terminal tail and the region between βB and helix B. In combinationwith the mutations in Mutant #4 (T23G and K81R) this is expected to havean increased impact on TR TYR20.

In relation to Mutant #18a(b)-1A (#4+P104E^(Gp)(D^(Gm))), the mutationof CR 104 (which is also an ACR), i.e. P104E^(Gp) or P104D^(Gm), isexpected to result in a new interaction with the backbone N of residue81. It is expected that the three mutations in the combined CM #18-1Awould have an increased impact on TR TYR20.

In relation to Mutant #19-1A (#4+D19P), residue 19 forms a salt bridgewith residue 21 (K or R) in cyanobacteria and plants, which is absent inred algae where residue 19 is P. It is expected that the mutation D19Pwill influence the reach of TR TYR20 into the active site, and that incombination with the Mutant #4 mutations, this would produce anincreased impact on TR TYR20.

These predictions are shown graphically in FIGS. 15 and 17.

The second example below relates to the identification of a major newmutational area (subregion 1B) which in turn led to the initialprediction of Mutant #20-1B (V116L/L117T/V121I/I138M/F140L). This mutanthas Mutant #8 (V121I/M297G/V300T), identified by the core method (Table3), as a component. As shown in Table 5, initial testing of Mutant #8showed improvement in specificity (5.6%) which providing a basis forfurther characterisation. Following identification of Sub-region 1B, asdescribed, examination of residue variations near residue 121 (CRadjacent to TR N123; see FIG. 16A) led to the discovery of a network ofinteractions between helix C and β-sheet E. This network may be seenmore clearly in FIG. 16B. Changes in this interaction network can affectthe orientation of TR N123. The interactions involve residues 116, 117,120, 121, 124, 133, 135, 138 and 140. Of these, residue 121 is a CR andresidues 120, 124, 133 and 135 are conserved in all major groups oforganisms (see FIG. 5). Residues 116, 117, 138 and 140 are DCRs, i.e.differ among the three major organism groups, red algae, cyanobacteriaand flowering plants (Table 2). It was observed that changes in the CRand DCRs interacting in this spatial region (i.e. 21, and 116, 117, 138and 140) appear to be compensating in the major organism groups. Thus,as an initial test of the effect of such changes on the orientation ofN123, Mutant #20-1B (V116L/L117T/V121I/I138M/F140L) was predicted (Table4).

Example 5 Generation of Mutant Rubiscos and Screening Thereof

Based on the ranked predicted Candidate Mutants in Tables 3 and 4,proof-of-principle studies were conducted by mutating the red-algalspecific residues into Region 1 of Synechococcus sp. PCC7942, in groupsof multiple mutations. Initially fourteen of the predicted LSU mutantsdetailed in Example 3 and listed in Table 3 (Mutants #1a, #1b, #4, #5a,#5b, #6a, #7a, #7b, #7d, #8, #9, #10, #12 and #14, where “a” and “b”refer to variants where the CR for G. partita or the ACR for G. monolis,respectively, were transplanted) were engineered by mutating theSynechococcus sp. PCC7942 rbcLS gene with the QuickChangemulti-mutagenesis kit (Stratagene) using appropriate primers. Inaddition, several mutants with single (#22-1A, #23-1A, #25, #26-1B) ordouble (#24) mutations, which are components of predicted mutants (#4,#8, #21-1A,B), were engineered as controls.

The genomic sequence for the rbcL-rbcS sequence (operon) of ‘wildtype’Synechococcus sp. PCC7942 is shown in SEQ ID No. 22. This sequence isthe same as for Synechococcus sp. PCC6301. In the native genomesequence, the rbcLS coding sequence reads ATG CCC (coding Met then Pro)but in all the cloned rbcLS sequences it is ATG GCC (coding Met thenAla). This nucleotide substitution was introduced to code for a uniquerestriction site (NcoI) used for cloning of the gene. A silent mutationin the second last codon (Arg) in the rbcSS sequence (CGA to CGC) wasalso introduced for cloning purposes. The translated sequence for thewildtype large subunit is shown in SEQ ID No. 24 and the translatedsequence for the wildtype small subunit is shown in SEQ ID No. 23. Thenucleotide and protein sequences for mutants are shown by SEQ ID NOS inTable 5, for example SEQ ID NOS: 25 and 26, respectively, for Mutant#1a.

After consideration of these initial results and development of theextended phylogenetic grafting method, a further four of the predictedLSU mutants detailed in Example 4 and listed in Table 4 (Mutant #17-1A,#18-1A, #19-1A, #21-1A,B) were engineered by the same method. All of thecontrol mutants (#22-1A, #23-1A, #24, #25, #26-1B) mentioned above arecomponents of these four mutants and are relevant, in particular, toMutants #4 and #21-1A,B. The nucleotide and protein sequences for thesemutants are shown by SEQ ID NOS in Table 5, for example SEQ ID NOS: 53and 54, respectively, for Mutant #17-1A.

The mutated rbcLS genes were sequenced before cloning back into thesecond expression plasmid which coded for the mutated LSU and the nativeSSU. The mutant Rubiscos were expressed and purified using a proceduredescribed in Example 6. These initial experiments on the eighteenSynechococcus sp. PCC7942 mutants and five control mutants showed goodexpression in E. coli of active (i.e. properly folded and assembledhexadecameric) mutant Rubiscos, with specificity and kinetic constantscomparable with, or better than, wild type, as described in Example 7.The way in which experimental test and optimisation procedures, detailedin Examples 6-11 are integrated with the prediction and in silicoscreening steps is shown in Flowchart 1. Flowchart 1 also shows howexperimental results may be fed back into the prediction procedure torefine the predictions of mutant proteins, followed by further cycles ofin silico screening and experimental screening and assessment of theimprovement in the functional property, in order to optimize it.

Example 6 Expression and Purification of Mutant Rubiscos

Although E. coli is the most widely used microbial host for expressingrecombinant DNA and proteins, obtaining the functional form of Rubiscofrom eukaryotic organisms (defined herein as “form I” protein) is morecomplex. As the holoenzyme of form I Rubisco is a hexadecamer made of 8large subunits (LSUs) and 8 small subunits (SSUs), it requiresappropriate chaperones to correctly fold and assemble the enzymecorrectly. Conveniently, however, when the operon coding for the Rubiscogenes (rbcLS and rbcSS) from Synechococcus sp. PCC7942 is expressed inE. coli both LSU and SSU subunits are abundantly synthesized. Hence,Synechococcus sp. PCC7942 was used here as the model L₈S₈ enzyme forinitial testing of the Rubisco predictions, and E. coli was used as thenatural choice of expression host for producing the mutant Rubiscos.

However, only about 1 to 5% of the expressed LSUs are correctly foldedand assembled into functional form with the amount of functional Rubiscoaccumulating to ˜1 to 3% (wt/wt) of the E. coli soluble protein.Purification of the functional Rubisco by traditional methods is alaborious and protracted process that may take up to 3 days.

The use of 6× Histidine (H₆) affinity tags is an attractive alternativethat could save substantial effort and time toward enzyme purification.But experiments have shown that fusion of H₆ tags to either termini ofthe LSU or SSU of form I Rubisco can compromise the catalytic activity.To overcome these difficulties, a recently adapted system (Baker et al.,2005, the entire contents of which are incorporated herein by reference)was used to simplify and speed up the purification of Synechococcus sp.PCC7942 Rubisco expressed in E. coli. This system involved theconstruction of a unique (pACYC-based) plasmid vector that incorporatesfusing in frame the coding sequence for a H₆-tagged ubiquitin (Ub)sequence (H₆Ub) to the 5′ end of rbcSS. The wild-type rbcLS in plasmidpTrcSynLS (that contains the PCC7942 rbcL-rbcS operon; Emlyn-Jones etal., 2006) was replaced with the mutated rbcLS (rbcLS*) and thenco-transformed into E. coli with the pACYC-based plasmid that codes forH₆Ub-tagged wild-type SSU (H₆Ub-SSU). When Rubisco subunit expressionwas induced with IPTG, all three Rubisco subunit peptides were produced(i.e. LSU, SSU and H₆UbSSU). Some were assembled into functional Rubiscohexadecamers made up of 8×LSU octameric cores and different ratios ofSSU (at most 8) and H₆UbSSU. Rubiscos with one or more H₆ tags wereeasily purified from other E. coli proteins using immobilized metalaffinity chromatography (IMAC) and the H₆Ub sequence then cleaved with aH₆Ub-specific protease which, along with unassembled H₆Ub peptides, maybe removed by IMAC. Using this method, purified Rubiscos were isolatedfrom the E. coli in approximately 1 hour.

Eighteen of the mutant Rubiscos and five control mutants specified inExample 5 and identified in Tables 3 or 4, as well as wild type, wereexpressed and purified using the above procedure.

Example 7 In Vitro Kinetic Assay of Mutant Rubiscos

Rubisco proteins purified using the method described in Example 6 wereused to measure the Michaelis constants for CO₂ (K_(c)) and substratesaturated carboxylation rates (V_(c) ^(max)) using ¹⁴CO₂-fixation assaysat 25° C., pH 8 according to the method described in Andrews (1988), theentire contents of which is incorporated herein by reference.

The purified enzyme was pre-incubated at 25° C. for 30 min in buffercontaining 20 mM MgCl₂ and 25 mM NaHCO₃, and K_(c) measurements wereperformed in nitrogen sparged septum capped scintillation vials. Thereactions were initiated by adding 10 μL of purified enzyme to 0.5 mL ofN₂-equilibrated assay buffer (100 mM EPPS-NaOH, 20 mM MgCl₂, 0.8 mMribulose-P₂, 0.1 mg/ml carbonic anhydrase) containing varyingconcentrations of NaH 4CO₃.

The Michaelis constants were determined by fitting the data to theMichaelis-Menten equation. Quantification of Rubisco content in theassays was measured using the [2-¹⁴C]carboxyarabinitol-P₂ (¹⁴2CABP)binding assay described by Ruuska et al. (1998) and Whitney and Andrews(2001). The substrate saturated carboxylation turnover rate (k^(c)_(cat)) was calculated by dividing the extrapolated maximal carboxylaseactivity (V_(c) ^(max)) by the concentration of Rubisco active sites inthe assay. The purified Rubisco preparations were also used to measurethe CO₂/O₂ specificity (S_(c/o)) at pH 8.3 as described in Kane et al.(1994).

A summary of the results obtained is presented in Table 5. Forspecificity, average results are given as % change compared with wildtype: a positive value represents an improvement. For kinetics, thevalues and % change compared with wild type are given; a positive %change for the catalytic rate k^(c) _(cat) and the catalytic efficiencyk^(c) _(cat)/K_(c) represents an improvement, while a negative % changefor the Michaelis constant K_(c) represents an improvement.

TABLE 5 Specificity and kinetic results for Synechococcus sp. PCC7942mutant Rubiscos. Kinetics S_(c/o) k^(c) _(cat)/K_(c) Average^(d) k^(c)_(cat) (s⁻¹) K_(c) (μM) (s⁻¹mM⁻¹) Mutant # (modified SEQ (% change (%change (% change (% change residue(s))^(c) ID^(e) wild type) wild type)wild type) wild type) Wild-Type 22-24 41.6 ± 0.7 13.2 ± 0.2^(a) 203 ±10^(a)  65^(a) 13.0 ± 0.2^(b) 197 ± 10^(b)  66^(b) #1a (Y25W, D51I^(Gp))25, 26 (3.4%) 11.5 ± 0.2^(a) 176 ± 6^(a)  65 (−13%) (−13%) (0%) #1b(Y25W, D51V^(Gm)) 27, 28 (−1.1%)  #4 (T23G, K81R) 29, 30 (10.0%)  14.1 ±0.2^(b) 198 ± 8^(b)  71  (8%)  (0%) (8%) #5a (G54A^(Gp), C84A, I87V) 31,32  (−6%) 11.3 ± 0.3^(a) 182 ± 12^(a) 62 (−14%) (−10%   (4%) #5b(G54S^(Gm), C84A, I87V) 33, 34 (1.9%) 10.6 ± 0.2^(a) 167 ± 8^(a)  63(−20%) (−18%)  (3%) #6a (T23G, Y25W, D51I^(Gp), 35, 36 (8.5%) 12.2 ±0.2^(b) 185 ± 9^(b)  66 K81R)  (−6%) (−6%) (0%) #7a (Y25W, D51I^(Gp),G54A^(Gp), 37, 38 (8.8%) 12.4 ± 0.2^(b) 195 ± 11^(b) 64 C84A, I87V) (−5%) (−1%) (−3%)  #7b (Y25W, D51I^(Gp), G54S^(Gm), 39, 40 (1.4%) n.m.n.m. n.m. C84A, I87V) #7d (Y25W, D51V^(Gm), 41, 42 (0.9%) n.m. n.m. n.m.G54A^(Gp), C84A, I87V) #8 (V121I, M297G, V300T) 43, 44 (5.6%) n.m. n.m.n.m. #9 (L36I, I116L, F140L) 45, 46 (3.6%) n.m. n.m. n.m. #10 (L36I,I116L, V121I, 47, 48 (2.9%) 10.8 ± 0.4^(b) 325 ± 27^(b) 33 F140L, M297G,V300T) (−17%) (65%) (−50%)  #12 (K18I, T23G) 49, 50   (1%) n.m. n.m.n.m. #14 (loop AKMGYW) 51, 52 (1.7%)  7.1 ± 0.4^(b) 260 ± 36^(b) 27(−45%) (32%) (−59%)  #17-1A (T23G, K18I, T68V, 53, 54 (−0.6%)  n.m. n.m.n.m. K81R) #18-1A (T23G, K81R, P104E) 55, 56 (−0.5%)  n.m. n.m. n.m.#19-1A (T23G, D19P, K81R) 57, 58 (−2.0%)  n.m. n.m. n.m. #21-1A, B(T23G, K81R, 59, 60 (−0.9%)  n.m. n.m. n.m. V121I, M297G, V300T) #22-1A(T23G) 61, 62 (5.0%) n.m. n.m. n.m. #23-1A (K81R) 63, 64 (7.0%) n.m.n.m. n.m. #24 (V121I, M297G) 65, 66 n.m. n.m. n.m. n.m. #25 (M297G) 67,68 n.m. n.m. n.m. n.m. #26-1B (V121I) 69, 70 n.m. n.m. n.m. n.m.^(a,b)refers to replicate measurements on different Rubisco samples doneon different days. ^(c)where given, specifies mutations are inSubregions 1A, 1A, B or 1B. ^(d)average of replicate measurements ondifferent Rubisco samples done on different days. ^(e)Sequence IDnumbers correspond to those in the sequence file. The numbers in the“SEQ ID” column correspond to the sequences on the computer-generatedsequence listings, n.m. represents not measured at time of filing.

Of the eighteen mutants and two single (control) mutants for whichspecificity measurements were made, all showed specificity comparablewith wild type, i.e. none was significantly impaired, while five mutantsand the two controls showed improvements of 5% or better. Of interest,four of these include the mutations T23G and/or K81R. Also, of interestis that mutants with ACR variants (#1a and #1b for position 51, #5a and#5b for position 54, and #7a, #7b and #7d for positions 51 and 54)showed significant differences (in the order of 8% for the Mutant #5 and#7 variants) demonstrating the sensitivity of specificity to thesechanges which spatially are relatively far from the active site (seeFIG. 10). The improvement in the S_(c/o) value of 5.6% in Mutant #8 wasnoteworthy as the mutations were in a different part of the N-terminaldomain (see FIG. 15) than most of the initial set of mutants predictedby the core method.

Of the 9 mutants for which k^(c) _(cat) was assayed, most showedslightly to significantly lower (i.e. poorer) values compared with wildtype with the exception, Mutant #4, which showed a significantimprovement of 8%. The corresponding 9 mutants assayed for K_(c)exhibited a range of values, with 4 showing moderately improved CO₂binding (#1a, #5a, #5b, #6a), 2 showing little change (#4, #7a) and 2showing significant impairment (#10, #14). The overall catalyticefficiency values (k^(c) _(cat)/K_(c)) similarly show a range of smallto significant improvement (#4, #5a, #5b), to little change (#1a, #6a,#7a) to significant impairment (#10, #12) when compared with wild type.It is notable that in tobacco (see Example 11), Mutant #23-1A showed asignificantly poorer k^(c) _(cat) value and also overall catalyticefficiency, whereas Mutant #4 showed significant improvements in allthree kinetic measures.

From the results of the initial set of mutants predicted by the coremethod (#1-#14), the stand-out mutants in terms of overall performancewere Mutants #4 and #6a, which showed improvements in specificity andkinetic efficiency of 10% and 8%, and 8.5% and 0%, respectively. Theproperties of the more complex mutant (#6a), which comprised themutations in #4 and #1a, were overall inferior to Mutant #4 (the bestmutant on the current list). This observation suggests that othermutations may be more advantageously grouped with those for Mutant #4than those of Mutant #1a. As discussed in Example 4, this observationprompted the development of the concept of Sub-regions and the extendedmethod, which led to the first predictions of Mutants #17-1A, #18-1A and#19-1A, as well as a more complex mutant including CRs from Sub-region1B also (#21-1A,B). The specificity results for these extended-methodpredictions showed little change compared with wild type.

Example 8 Directed Evolution of Synechococccus mutants in E. coli

The phylogenetic grafted mutants represent one “directed” strategy forexploring regions of sequence space not sampled naturally. However anyincrease in the activity of these mutants may be impaired due to someareas of “poor sequence fits”, as they may not be optimized for the hostRubisco structure. Although the extended phylogenetic grafting methodprovides a rational in silico strategy which may be used for optimising“lead” mutants, including relieving steric conflicts by recruitment ofSvRs and other naturally occurring variant residues which may beidentified as complementary to mutations in the “leads”, an alternativeoption to minimize the effects of these conflicts may be to use anexperimental directed evolution method to optimize them, i.e. to usethese partially optimized Rubiscos as starting points. These mutantsalso provide in themselves a novel starting point for directed evolutionas they have different potential for exploring sequence space comparedwith wild type.

As detailed in Example 6, unlike all other Form I Rubiscos (i.e.hexadecameric) from eukaryotic organisms, Rubisco from SynechococcusPCC7942 can assemble correctly in E. coli and has been chosen for amutant screening procedure. Using methods described in Examples 5-7,Candidate Mutant predictions (which may include groups of correlatedmutations, and independent mutations in different structural regionssurrounding the Target Residues) can be screened initially in E. coli toconfirm they are active and to obtain in vitro kinetic constants forcomparison against each other and wild type. Mutants with up to 10-12mutations can be produced routinely using the current technology. Asdetailed in Examples 5-7, selected single mutants can be made to testthe general hypothesis underlying the phylogenetic grafting method thatsingle mutants are likely to be poorly active/inactive, and that atleast two correlated mutations are necessary to produce an acceptablyactive enzyme.

A system suitable for directed evolution of Rubisco in E. coli hasrecently been reported (Mueller-Cajar et al., 2007). This uses anengineered E. coli strain, MM1, whose growth can be made dependent onfunctional expression of Rubisco, when co-expressed withphosphoribulokinase (PRK). Glycolysis in MM1 was blocked by deletion ofthe glyceraldehyde 3-phosphate dehydrogenase gene (gapA) and a metabolicbypass shunt comprising a Synechococcus PRK and Rhodospirillum rubrumRubisco was introduced. As a result, MM1 is dependent on functionalRubisco expression to metabolize the product of PRK catalysis,ribulose-1,5-bisphosphate, that is toxic to E. coli.

This general method may be used to evaluate whether Rubiscos withsignificantly enhanced activity can be more efficiently evolved startingfrom inactivated forms of the most promising Synechococcus sp. PCC7942grafted mutants detailed in Example 7 and Table 5. For this purpose,randomly mutagenised libraries (made using methods reported byMueller-Cajar et al., 2007) of these inactivated genes may betransformed into MM1 cells grown under differing selective conditions(e.g. varying the growth CO₂/O₂ pressures, changing the extent of PRKproduction). Colonies expressing evolved Rubisco variants with improvedfitness (i.e. those that survive the screen) may be isolated, sequencedand the kinetics of the purified mutated Rubiscos characterised asdetailed in Example 7.

Example 9 Testing Biochemical and Physiological Competence ofSynechococcus Mutants In Vivo

The in vitro functional tests in Example 7 identified severalSynechococcus mutants with improved Rubisco activity, and which also,necessarily, were, thus, correctly folded and assembled when expressedfrom the E. coli expression system and purified as described in Example6. In the Rubisco re-engineering strategy, Synechococcus has been usedas the most convenient initial host for experimental test of mutantpredictions to identify “lead” candidates. Due to recent advances inengineering mutant Rubisco in a model plant, tobacco, using plastidtransformation, as described in Example 10, in the work described here aCandidate Mutant (#4) identified as a promising Synechococcus mutant wastested directly in the test flowering plant (tobacco) withoutundertaking the intermediate step, shown in Flowchart 1, of confirmingthat it can be acclimated back into its native host (Synechococcus)without detriment to its phenotype. This improved method allowedassessment of the assembly and kinetics of mutant Rubiscos in tobaccowithin 7-9 weeks which is faster than that required to obtain and growcyanobacteria transformants. Where the ultimate purpose of mutantdevelopment is for engineering improved Rubisco in plants, this strategywould be preferred. However, if the ultimate purpose is for engineeringimproved Rubisco in cyanobacteria, then it is preferred to perform thisphysiological-test step in Synechococcus to assess whether catalyticallybeneficial mutations might introduce incompatibility problems thatperturb productive folding-assembly by cyanobacterial chaperonecomplexes or other interacting proteins such as those involved incarboxysome formation. A method for performing these tests inSynechococcus is described below.

In Synechococcus sp. PCC7942, the Rubisco genes (rbcLS and rbcSS) arecoded by a single operon on the chromosome (of which there are typically5 chromosome copies per cell) and, analogous to E. coli, thiscyanobacterial strain is naturally competent and can be geneticallytransformed either by targeted modifications to its chromosome (e.g.gene deletion, gene substitution) by homologous recombination or bystable retainment of plasmid shuttle vectors within its cells.

Synechococcus PCC7942 mutant strains have been developed (seeEmlyn-Jones et al., 2006 and Price et al., 1993 for examples). ASynechococcus PCC7942 mutant strain in which the chromosomal rbcLS-rbcSSoperon is deleted (i.e. a 7942ΔrbcLS strain) may be used to facilitatethe re-introduction of mutant Rubisco rbcLS-rbcSS genes. AsSynechococcus sp. PCC7942 cannot grow heterotrophically (i.e. on anexternal carbon source) and requires a Rubisco for growth, 7942ΔrbcLSstrains can be generated by: (1) introducing a second Rubisco gene (e.g.rbcM coding for the structurally different Form II Rubisco homodimer(L₂) from the bacterium Rhodospirillum rubrum or the native L₈S₈ PCC7942Rubisco) on a plasmid shuttle vector into Synechococcus sp. PCC7942 then(2) homologously recombining in an antibiotic resistance gene km^(R) toreplace the rbcLS-rbcSS operon in each chromosome copy (i.e. so themutation can be fully segregated). Synechococcus PCC7942 cellstransformed with rbcM expressed on a shuttle vector can be subsequentlytransformed with another plasmid to homologously replace the chromosomalrbcLS-rbcSS coding region with a km^(R) gene. Upon isolation ofcompletely segregated ΔrbcLS-rbcSS::km^(R) transformants (i.e. all thechromosomes have rbcLS-rbcSS replaced with km^(R)) the PCC7942ΔrbcLScells may be used to homologously re-introduce the mutated rbcLS* andrbcSS genes and the cells cured of the shuttle vector.

Using established techniques (e.g. see Emlyn-Jones et al., 2006), thephenotype of the transformed cells may then be comprehensivelycharacterised biochemically, for example, assessing whether the mutatedRubisco LSU subunits are readily folded and assembled properly, andphysiologically, for example, assessing whether there are differences inphotosynthetic capacity, inorganic carbon partitioning or growth rate.

Example 10 Generation of Rubisco Plastome Transformants in Tobacco

A strategy for re-engineering Rubisco which is applicable to higherplant Rubiscos is by plastome transformation using mutated rbcL* genes.The plastome of tobacco is readily transformable (Andrews and Whitney,2003) and was used as a model to conduct proof-of-principle tests forthe transformation of other plants.

The most promising Synechococcus Rubisco Mutant #4 was used as theinitial test case. The component single mutants, T23G (Mutant #22-1A),and K81R (Mutant #23-1A), and the more complex mutant #6a (T23G, Y25W,E51I, K81R) were also tested. The nucleotide and protein SEQ ID NOS fortobacco Mutants #4, #22-1A, #23-1A and #6a are given in Table 6. Asthese residues are Candidate Residues (see Table 2) these same mutationswere used in tobacco as in Synechococcus.

Transplastomic tobacco lines are available which allow more rapidscreening of the kinetics of mutated tobacco Rubiscos than thetraditional lengthy chloroplast transformation methods in which thenative rbcL genes in the plastome are substituted with mutated versions(Andrews and Whitney, 2003 (supra)) using the biolistic transformationtechnique described in Svab and Maliga (1993). In a recent improvementto the method for transforming mutated or foreign rbcL genes back intothe tobacco plastome the native rbcL gene was replaced with the rbcMgene from Rhodospirillum rubrum and the aadA selectable maker gene(coding for spectinomycin resistance) and then the aadA gene removed toproduce marker-free (ΔaadA) tobacco-rubrum transplastomic lines.(Whitney and Sharwood, 2008, the entire contents of which areincorporated by reference) These lines were generated by biolisticallytransforming the plastome of wild-type tobacco (Nicotiana tabacum L. cvPetit Havana [N,N]) with plasmid p^(cm)trLA (Genbank accession numberAY827488). The aadA gene in the transformants is flanked by 34-bp loxPsites that enable its excision by CRE-lox recombination. To excise aadA,leaves from a p^(cm)trLA-transformed line were biolistically bombardedwith the CRE expressing plasmid pKO27 (Corneille et al., 2001). Thebombarded leaves were dissected (˜0.5 cm²) and propagated inkanamycin-selective medium (agar-solidified Murashige-Skoog saltscontaining 3% (w/v) sucrose, 15 μg ml⁻¹ kanamycin and hormones (Svab andMaliga, 1993). The first plantlets to emerge from the bleached bombardedleaf sections were transferred to MS medium (selective medium withoutkanamycin or hormones) and loss of aadA confirmed by routine PCRanalyses.

The ΔaadA tobacco-rubrum lines permit re-use of the aadA marker gene forsubsequently transforming its plastome, such as re-transforming back inmutated tobacco rbcL* variants to replace rbcM. The transformationefficiency of replacing rbcM in the ΔaadA tobacco-rubrum with variantrbcL* genes is 3 to 10-fold higher than transforming wild-type tobacco,and is immune to unwanted recombination events that may occur whentransforming rbcL* genes into wild-type tobacco plastomes. The methodallowed the production of transformants containing onlyrbcL*-transformed plastome copies (i.e. homoplastic transformants)within 6 to 8 weeks as the plastome copies containing the rbcM gene wererapidly eliminated. As the R. rubrum Rubisco is a small homodimer ofLSUs (L₂, ˜100 kDa), rbcL*-transformed lines producing the larger form 1L₈S₈ Rubiscos (˜520 kDa) may be identified by separating the solubleleaf protein by non-denaturing polyacrylamide gel electrophoresis asdescribed in Whitney and Sharwood (2007) and homoplasmicity measured bythe absence of L₂ Rubisco.

This system is potentially adaptable to other plants where plastidtransformation has been reported. The genetic transformation of plastidsin a variety of different plants has been reported, for example in Koopet al. (1997), the entire contents of which is incorporated herein byreference.

A straightforward variation of the transformation system (Whitney andSharwood, 2008) offers the potential to rapidly test the kinetics ofpredicted mutant Rubiscos of other flowering plants or crops of interestwithout performing a full plastid transformation in the plant ofinterest itself. Sharwood et al. (2008), the entire contents of which isincorporated herein by reference, have shown that the rbcL gene ofanother plant (sunflower) can be successfully transformed into the ΔaadAtobacco-rubrum line to produce active chimeric Rubisco consisting ofsunflower LSUs and tobacco SSUs, which can be isolated and characterizedkinetically. Its kinetic parameters mimic those of sunflower Rubisco.Use of this method would allow development and optimisation of Rubiscophenotype for a range of mutants of different plants of interest, usingthe convenient tobacco transformation model.

Mutations for Mutants #4, #22-1A, #23-1A and #6a were made to thewild-type tobacco (Nicotiana tabacum) plastome rbcL coding sequenceusing the QuickChange multi-mutagenesis kit (Stratagene) usingappropriate primers, and introduced into the tobacco plastometransforming plasmid pLEV1 where selection of transformants isfacilitated by the incorporation of a promoter-less aadA gene downstreamof rbcL (Whitney et al., 1999). The pLEV1-derived transforming plasmidscoding the mutagenized tobacco rbcL* copies with the nucleotidesequences coding for Mutants #4, #22-1A, #23-1A and #6a, as well as wildtype, were biolistically transformed into a ΔaadA tobacco-rubrum lineand spectinomoycin-resistant plantlets selected as described (Svab andMaliga, 1993). Transformants where the rbcM had been replaced with therbcL* or rbcL genes were identified by the production of L₈S₈ Rubiscousing non-denaturing polyacrylamide gel electrophoresis. A sample gelfor transformants for wildtype, and Mutants #4 and #23-1A is shown inFIG. 20; comparable data (not shown) were obtained for Mutants #22-1Aand #6a.

Example 11 Biochemical Characterization of Tobacco Rubisco Transformants

The following methods were used to extract and purify Rubisco expressedin homoplasmic transplastomic and wild-type tobacco cells to carry outkinetic analyses.

Radiolabeled 14CO₂ fixation assays were used to measure the substratesaturated turnover rate (k_(c) ^(cat)) and Michaelis constant for CO₂ at0% (K_(c) ^(0%)) or 21% O₂ (K_(c) ^(air)) using soluble leaf proteinextract. Leaf discs (˜1 cm²) were taken during the photoperiod andextracted on ice using glass homogenisors (Wheaton, USA) into 0.8 mlCO₂-free extraction buffer (50 mM Bicine-NaOH, pH8.0, 1 mM EDTA, 2 mMDTT, 1% (v/v) plant protease inhibitor cocktail (Sigma-Aldrich) and 1%(w/v) PVPP). The sample was centrifuged (36,000 g, 5 min, 4° C.) and thesoluble protein incubated (activated) with NaHCO₃ and MgCl₂ (15 mM each)for 15 min and used to measure Rubisco content in duplicate aliquotsincubated with 40 μM of 142-CABP and the amount ofRubisco-bound-¹⁴2-CABP recovered by gel filtration (Ruuska et al.,1998), or used to measure K_(c) ^(0%) and K_(c) ^(air) at 25° C., pH 8.0using ¹⁴CO₂ fixation assays (Andrews 1988; Whitney and Sharwood, 2007).To confirm the samples used were homoplasmic (i.e. only contain plastomecopies transformed with the rbcL* genes and none with rbcM) the proteinwas also separated on non-denaturing polyacrylamide gels (FIG. 20). Asfor the wild-type controls, only mutated L₈S₈ Rubisco and no L₂ Rubiscowas expressed in the Mutant #4 and #23-1A transformants.

The kinetic assays were initiated by adding activated soluble proteinextract into septum capped scintillation vials containing either N₂ (forK_(c) ^(0%)) or CO₂-free air (for K_(c) ^(air)) equilibrated assaybuffer (100 mM Bicine-NaOH, 15 mM MgCl₂, 0.6 mM ribulose-P₂, 0.1 mg·ml⁻¹carbonic anhydrase) containing 0 to 90 μM ¹⁴CO₂. Ribulose-P₂ wassynthesized according to (Kane et al., 1998). The assays were stoppedafter 1 min with 0.5 volumes of 25% (v/v) formic acid, the reactionsdried at 80° C. and the residue dissolved in water, two volumes ofscintillant were added, vortexed, and ¹⁴C measured by scintillationcounting. K_(c) ^(0%) and K_(c) ^(air) were calculated from theMichaelis-Menten plot of carboxylation rate versus [CO₂].

Measurements of k_(c) ^(cat) were calculated using comparable ¹⁴CO₂fixation assays containing 15 mM NaH ¹⁴CO₃ and dividing the substratesaturated carboxylation rate, V_(c) ^(max), by the concentration ofRubisco active sites measured by 142-CABP binding (see above).

Specificity measurements were done using purified Rubisco. Soluble leafprotein was extracted as described above and 0.2 mL chromatographedthrough a Superdex 200HR 10/30 column equilibrated with specificitybuffer (30 mM Triethanolamine pH 8.3, 30 mM Mg acetate) using an ÄKTAexplorer system (APBiotech). The three peak fractions (0.3 ml)containing L₈S₈ Rubisco were pooled (˜100-150 pmol L-subunit sites) andused to measure CO₂/O₂ specificity at 25° C. as described (Kane et al.,1994) after equilibrating with an atmosphere containing 500 ppm CO₂ inO₂ controlled using three Wösthoff precision gas-mixing pumps.

A summary of the results obtained is presented in Tables 6 and 7. Forspecificity, average results are given as % change compared with wildtype: a positive value represents an improvement. For kinetics, thevalues and % change compared with wild type are given; a positive %change for the catalytic rate k^(c) _(cat) and the catalytic efficiencyk^(c) _(cat)/K_(c) represents an improvement, while a negative % changefor the Michaelis constant K_(c) (in air or 0% O₂) represents animprovement.

TABLE 6 Specificity and kinetic results measured in air (O₂ 21%) forTobacco mutant Rubiscos. kinetics S_(c/o) k^(c) _(cat)/K_(c) ^(air)Mutant # Average^(a) k^(c) _(cat)/(s⁻¹)^(a) K_(c) ^(air) (μM) (s⁻¹ mM⁻¹)(modified Seq (% change (% change (% change (% change from residue(s))ID^(b) from wildtype) from wildtype) from wildtype) wildtype) wild-type71, 72 81.0 ± 1.6 3.2 ± 0.1 24.1 132 #4 (T23G, K81R) 73, 74 77.6 ± 2.83.6 ± 0.1 20.4 176 (−4%) (13%)  (−15%) (33%) #23-1A (K81R) 75, 76 76.1 ±3.4 3.5 ± 0.1 23.8 147 (−6%) (9%)  (−1%) (11%) #22-1A (T23G) 77, 78 76.2± 1.0 3.5 ± 0.1 20.5 173 (−6%) (9%) (−15%) (31%) #6a (T23G, Y25W, 79, 8066.4 ± 4.4 3.5 ± 0.1 19.4 179 E51I, K81R) (−18%)  (9%) (−20%) (36%)^(a)Average or calculated value from measurements made on 3 separateprotein assays ± S.D. ^(b)Sequence ID numbers correspond to those in thesequence listing; the first number is the nucleotide SEQ ID NO and thesecond number is the protein SEQ ID NO.

The results in Table 6 for measurements in air (21% O₂) show significantdifferences in specificity and kinetic parameters for the differentmutants. Significant improvements over wild type are evident in bothk^(c) _(cat) and K_(c) ^(air) values for Mutant #4 (T23G, K81R) of 13%and −15%, respectively, producing an overall improvement in catalyticefficiency of 33%. These can be compared with k^(c) _(cat) values of 9%,i.e. less improvement, and K_(c) ^(air) values of −1%, −15% and −20%,i.e. minimal (#23-1A) or similar improvement, for the single Mutants#23-1A (K81R) and #22-1A (T23G), and Mutant #6a (T23G, Y25W, E51I, K81R)which includes these two mutations. These translate into comparableimprovement in catalytic efficiency of 31 and 36%, respectively, for#22-1A and #6a, but only 11% for #23-1A. The kinetic results (triplicateassays) were obtained using soluble leaf protein extracted from two orthree different transformants for wildtype and mutants. The replicateisolated Rubiscos gave similar results, contributing to the small errorsof the measurements.

The specificity results for Mutant #4 show a modest impairment (−4%)compared with wild type, while both the single mutants, #22-1A and#23-1A show slightly greater impairment (−6%). However, the specificityfor Mutant #6a is greatly impaired (−18%. These values were obtainedfrom triplicate measurements, as shown in Table 6, using differentpurified Rubiscos from two wildtype and two of each of the mutanttransformants.

Consideration of the specificity and kinetic results together indicatesthat the improvement in carboxylation efficiency has been matched by acomparable improvement in oxygenation efficiency for Mutant #4, but muchgreater improvement for #6a. As an initial test of whether changes inoxygenation efficiency might be due to changes in k^(o) _(cat) or K_(o),K_(c) ^(0%) was measured in 0% O₂. These results, given in Table 7, showthat all the mutants have poorer K_(c) ^(0%) values than wild type, 10,30, 18 and 5%, respectively, for #4, #23-1A, #22-1A and #6a, but thatthe deterioration in the K_(o) (i.e. K_(i)(O₂)) values are muchgreater—87%, 92%, 133% and 89% higher, respectively. The significantlyhigher K_(o) values for the mutants compared with wild type indicatethat the mutants are less inhibited by O₂. Values for K_(o) werecalculated according to Whitney et al. (1999). The improved oxygenationefficiency is explained by the values for k^(o) _(cat) shown in Table 7,which show significant improvements of 201%, 173%, 234% and 241%,respectively for mutants #4, #23-1A, #22-1A and #6a compared withwildtype.

TABLE 7 Specificity and kinetic results measured in 0% O₂ for Tobaccomutant Rubiscos. kinetics k^(c) _(cat) (s⁻¹) K_(c) ^(0%) (μM) k^(c)_(cat)/K_(c) ^(0%) k^(o) _(cat)(s⁻¹) (% change (% change (s⁻¹ mM⁻¹) (%change Mutant # (modified from wild from wild (% change from K_(i)(O₂)from wild residue(s)) type) type) wild type) (μM) type) wild-type 3.2 ±0.1 ^(a) 12.2 ± 0.4 ^(b) 262 259 ± 23 ^(b) 0.83 ^(d) #4 (T23G, K81R) 3.6± 0.1 ^(a) 13.4 ± 0.5 ^(b) 269 485 ± 56 ^(b) 1.67 ^(d) (13%)  (10%) (3%)(87%) (201%) #23-1A (K81R) 3.5 ± 0.1 ^(a) 15.8 ± 0.4 ^(a) 222 497 ± 70^(a) 1.44 ^(d) (9%) (30%) (−15%)  (92%) (173%) #22-1A (T23G) 3.5 ± 0.1^(a) 14.4 ± 0.7 ^(c) 243  603 ± 120 ^(c) 1.94 ^(d) (9%) (18%) (7%)(133%)  (234%) #6a (T23G, Y25W, 3.5 ± 0.1 ^(a) 12.8 ± 0.5 ^(a) 273 490 ±68 ^(a) 2.00 ^(d) E51I, K81R) (9%)  (5%) (4%) (89%) (241%) ^(a) Averageor calculated value from measurements made on 3 separate protein assays± S.D. ^(b) Calculated value from measurements made on 4 separateprotein assays ± S.D. ^(c) Calculated value from measurements made on 2separate protein assays ± S.D. ^(d) Calculated using the equationS_(c/o) = (k^(c) _(cat)/K_(c))/(k^(o) _(cat)/K_(o))

In summary, the results show that Mutant #4 retains its superiorproperties in tobacco, although they are expressed more as improvementsin catalytic efficiency than as roughly equal improvements inspecificity and efficiency, as is the case for the Synechococcus Mutant#4. Although Mutant #6a shows comparable catalytic efficiency to Mutant#4, it has significantly impaired specificity S_(c/o).

Example 12 Simulation of Phenotype of Tobacco Rubisco Transformants

Results for Synechococcus and tobacco mutants in Tables 5 and 6 show arange of levels of improvements in key kinetic parameters (S_(c/o),k^(c) _(cat), K_(c)) compared with wildtype. These parameters are alsoexpected to show different temperature dependence compared withwildtype. Thus, for each branch of photosynthetic organism the mutantsshow different profiles of improvements in the kinetic parameters, thatis there is a range of percentage changes in the components of theparameter set {S_(c/o), k^(c) _(cat), K_(c)} for a given mutant. Thisparameter set is termed Rubisco phenotype.

The rate of CO₂ assimilation in C₃ plants reflects Rubisco's kineticproperties and content in the plant (Farquhar et al., 1980; vonCaemmerer, 2000). This correlation has been validated for mutant,foreign-transformant or differently expressed tobacco Rubiscos. Methodsfor simulating CO₂ assimilation under variable growth conditions, suchas CO₂ concentration, water, nutrients, temperature and light intensity,have been used to predict photosynthetic performance in leaves usingRubisco kinetic data for a range of plants (von Caemmerer, 2000, theentire contents of which are incorporated herein by reference). Ananalogous study of performance within the leaf canopy of the whole planthas been reported (Zhu et al., 2004, the entire contents of which areincorporated herein by reference). By these means it is possible topredict how a plant with a given Rubisco and Rubisco phenotype, asdetermined by kinetic measurements in vitro, would perform underdifferent sets of growth conditions in planta. There is also extensiveexperimental evidence that increases in leaf photosynthesis aretranslated into increases in biomass and crop yield. Together thesestudies have shown that increased efficiency of photosynthesis fromimproved Rubiscos benefits plant growth, improves water-use efficiencyand increases the C/N ratio.

FIGS. 21 to 24 contain plots illustrating use of these models to predictplant phenotype, including examples of mutant tobacco Rubisco phenotypethat have been produced by the inventors (Table 6) or within a similarrange of improvements in Synechococcus, as in Table 5.

FIG. 21 provides a plot for wildtype tobacco growing under normalconditions. It shows that the carbon assimilation rate (A) is limited atlower leaf internal CO₂ concentrations (C_(i)) by Rubisco carboxylaseactivity (dependent on k^(c) _(cat), K_(c) and amount of enzyme) and athigher leaf internal CO₂ concentrations by electron-transport relatedfactors (light, Rubisco specificity determining photorespiration, andRuBP regeneration rate). The region of the plot of interest is thatspanning the range of CO₂ concentrations experienced in the chloroplast,i.e. from the atmospheric level of 380 μbar (C_(a)) downwards: thisregion is shown boxed. Under these normal growing conditions, thecross-over point (*) between Rubisco-limited and electron-transportlimited growth is at a C_(i) value of ˜340 μbar; thus, under normalconditions, growth is Rubisco-limited. The leaf internal CO₂concentrations of C_(i)(1) and C_(i)(2) at values of ˜230 and 300 μbarcorrespond to stomatal conductances representing drought and averagewater-use conditions, respectively (as determined by von Caemmerer,2000). It is clear that under drought, carbon assimilation is reduced byapproximately 25% (A₁ compared with A₂)

FIG. 22 shows the predicted effect of variation in four growthconditions (water availability, nitrogen and light limitations, andtemperature) for wildtype tobacco on the rate of CO₂ assimilation.Nitrogen limitation has been modelled as reduction of Rubisco content;as Rubisco constitutes 30-50% of chloroplast protein, nutrientlimitation has a direct effect on photosynthetic capacity by limitingRubisco biosynthesis. Again considering the positions of the plot withrespect to the relevant range of CO₂ concentrations (shown boxed) andthe cross-over points (*) between Rubisco-limited and electron-transportlimited growth, it is apparent that A is Rubisco-limited under allconditions except low light (I=400 μmol quanta m⁻² s⁻¹; FIG. 22C) andhigh T (35° C.; FIG. 22D) where it is electron-transport limited. Nocross-over points (*) are shown on the plots in FIG. 22B for 60% and 30%Rubisco content as they are beyond 500 μbar.

In FIG. 23, the key features of FIGS. 21 and 22 are combined in plotswhich show how hypothetical improvements in the key kinetic parameters(S_(c/o), k^(c) _(cat), K_(c)) compared with wildtype tobacco translateinto enhanced carbon assimilation rates. These plots provide a pictureof the general level of biomass increase which could be achieved forspecific Rubisco mutant phenotypes under various limiting growthconditions; they thus provide guidance as to the most appropriate growthconditions for a particular mutant. Dotted lines represent the mutantpredictions.

Plots in FIG. 23A for mutant tobacco with a hypothetical 25% improvementin S_(c/o) (no change in k^(c) _(cat), K_(c)) show greatest enhancementsin A compared with wildtype at high T (9% at 35° C.) and low light (11%at I=400) under drought conditions (C_(i)=230 μbar), with slightly lowerenhancements under average water-use (6% and 9%, respectively). Thesevalues should be compared with the small enhancements under normal T(25° C.) and light (I=1000) levels of 4% and 3% under drought andaverage water-use conditions, respectively.

Plots in FIG. 23B for mutant tobacco with a hypothetical 25% improvementin k^(c) _(cat) (no change in S_(c/o), K_(c)) show greatest enhancementin A compared with wildtype at normal and low T (18% at 25° C.; 14% at15° C.) under drought, but with much lower values under averagewater-use conditions (5%, 2% for T=25, 15° C.). Consistent with A beingRubisco-limited within the relevant range of C_(i) values (230-300 μbar)except for the mutant at 100% Rubisco content, the plots for effective Nlimitation (reduced Rubisco) show greatest enhancement at the lowestRubisco contents (27% at content=30%; 23% at content=60%) over thisC_(i) range. However, interestingly, for normal (100%) Rubisco contentwhere the cross-over point changes greatly for the mutant, there is alarge variation in enhancements between drought and average water-useconditions of 18% and 5%, respectively. This mutant phenotype shows verylarge differences in enhancements under varying light conditions,particularly as a function of water availability. The latter dependencecan be deduced from large shifts in cross-over points for the mutant atI=1000 and 1600 towards electron-transport limited carbon assimilationover the accessible CO₂ concentration range (shown boxed). Thus, theenhancements range from zero at low light (I=400) to 18% and 19%,respectively, under drought at I=1000 and 1600, but 6% and 12%,respectively, under average water usage.

Plots in FIG. 23C for mutant tobacco with a hypothetical 25% improvementin K_(c) (no change in S_(c/o), k^(c) _(cat)) show similar trends tothose in FIG. 23B. In this case the change in K_(c) again shifts thecross-over point (*) between Rubisco-limited and electron-transportlimited growth towards the latter at normal and low T's and normal andhigh light, but the shift is not as great as for the k^(c) _(cat)mutant. This results in only small dependencies of the enhancements onwater availability for varying T, light and Rubisco content. Thus, atnormal and low T the enhancements are 8% and 10% under drought and 8%and 7% under average water use, with little change (3%) at high T.Similarly, at normal and high light, enhancements are both 8% underdrought and average water-use conditions, with only small changes (4-5%)at low light. Enhancements under effective N limitation are also thesame under drought and average water-use conditions, with values of 8%,10% and 11% for 100%, 60% and 30% Rubisco content, respectively. Notethat in this simulation, the K₀ value was not changed; this was done formutant examples in FIG. 24.

In FIG. 24, the analyses are extended to model the change in carbonassimilation rates for tobacco mutants #4, #23-1A and #6a, using kineticparameters from Tables 6 and 7.

The plots for mutant #4 in FIG. 24A show enhancements in A modelled withthe kinetic profile of {S_(c/o)=−4%; k^(c) _(cat)=+13%; K_(c)=+10%;K_(o)=+87%). As for the models with k^(c) _(cat)=+25% and K_(c)=−25% inFIG. 23, the cross-over points (* and ♦, for wildtype and mutantrespectively) between Rubisco-limited and electron-transport limitedgrowth are shifted towards the latter for the mutants at normal and lowT's and normal and high light, resulting in greater variation in levelsof enhancements under given growth conditions. Thus, at normal and low Tthe enhancements are 15% and 11% under drought but 4% and 0% underaverage water-use conditions, with negligible change at high T.Similarly, at normal and high light, enhancements are 15 and 23%,respectively, under drought, but 4 and 10%, respectively, under averagewater-use conditions, with little change at low light. Largeenhancements are also observed under effective N limitation, but withlittle dependence on water availability, i.e. 33% and 31% under droughtand average water-use conditions, respectively, at a Rubisco content of30% compared with 15% and 4% at normal Rubisco content, respectively.Overall, Mutant #4 is thus predicted to display strong enhancementsunder normal growth (T, I, N) conditions for varying water availability(15 to 4%), under drought conditions at low T (11%), under high light(23%), and under N depletion (33% at 30% Rubisco content).

The effectiveness of the double mutation in tobacco mutant #4 inenhancing carbon assimilation, may be seen from analogous modelling ofthe kinetic data (Tables 6 and 7) of mutant #23-1A, which contains oneof its mutations (K81R). Mutant #23-1A has been modelled with thekinetic profile of {S_(c/o)=−6%; k^(c) _(cat)=+9%; K_(c)=+30%;K_(o)=+92%). Compared with the results in FIGS. 23B, 23C and 24A, theplots in FIG. 24B show the cross-over points (♦) for the mutant arestill shifted to electron-transport limited growth but to a lesserextent. Consequently, the improvements are more modest. For example, 9and 3% under drought and average water-use conditions, respectively, atnormal T and light. The best performance is again under effective Nlimitation, with ˜11% at 30-60% Rubisco content under both drought andaverage water-use conditions.

The third set of predctions, shown in FIG. 24C, is for tobacco mutant#6a, which contains four mutations, including those in mutant #4. Mutant#6a has been modelled with the kinetic profile of {S_(c/o)=−18%; k^(c)_(cat)=+9%; K_(c)=+5%; K_(o)=+89%) from Tables 6 and 7. Compared withthe results in FIG. 24A, the plots in FIG. 24C show that the cross-overpoints (♦) for the mutant are shifted more towards electron-transportlimited growth, but the effects on improvements are more modest than formutant #4. This is a consequence of the much poorer specificity. On thebasis of kinetic parameters, mutant #6a is slightly more efficient than#4 (36% v. 33%) but shows different patterns of k^(c) _(cat) (9 v. 13%,i.e. poorer) and K_(c) (+5% v. +10%. i.e. better). Under normalconditions (T, I, N), the performance of mutant #6a is improved by 6%under drought but impaired by 3% under average water-use conditions. Thebest performance is under effective N limitation (30-60% Rubisco) withimprovements of 20-27% under both drought and average water-useconditions.

In summary, this analysis demonstrates that particular improved mutantRubisco phenotypes may be more suitable for particular growingconditions. The methods described herein provide the capability toproduce mutant Rubiscos with kinetic profiles optimized for particularpreferred plant growing conditions. It is expected that particularRubisco phenotypes will show a range of benefits in the phenotype of theplant, such as faster growth rate and shorter time to flowering, lowerrequirements for water and/or nitrogen fertilizer, or ability to growefficiently at higher temperatures. These are expected to translate intoincreased productivity of plant growth (and grain production) undergrowth conditions such as drought and/or heat stressed environments (hotarid climates), nutrient-poor soils, or low-light conditions with ashort growing season (higher latitudes). Accordingly, the methodsdescribed in this example allow the prediction of the rate of CO₂assimilation by a plant expressing a Rubisco, such as a mutant Rubiscoproduced by methods described herein, by modelling based on parametersfor Rubisco functional properties obtained by in vitro measurements. Themethods described in this example thus allow the prediction of plantperformance under both optimal growth conditions and sub-optimal growthconditions, such as where illumination, water, or nitrogen are limiting,or where temperature is elevated.

Example 13 Experimental Characterization of Phenotype of Tobacco RubiscoTransformants

Homoplasmic transplastomic lines and wild-type tobacco controls aregrown to maturity in soil in controlled environment growth chambers orglass houses and standard physiological tests are undertaken (asdescribed in Whitney et al, 1999; Whitney and Andrews, 2001; and Whitneyet al., 2001, the entire contents of which are incorporated herein byreference). Tests comprise an assessment of growth rate, biomassproduction, leaf index area, Rubisco mRNA and protein content, carbon tonitrogen rations of plant leaves, starch content, and photosyntheticperformance.

These tests are performed under both optimum (high light, non limitingwater and nutrients, temperature set at 25° C.) or resource-limitingconditions (e.g. reduced N, water or CO₂) or elevated temperatures.Tests under optimum conditions assess differences in various growth(e.g. exponential growth rate, biomass, leaf area index), biochemical(e.g. Rubisco mRNA and enzyme content, leaf C:N ratio, starch content)and metabolite (e.g. RuBP:PGA) indices. Tests under limiting conditionsassess the performance of the mutants under growth conditions mimickingenvironmental stress, such as drought and/or heat stress (hot aridclimates), nutrient-poor soils, or low-light conditions with a shortgrowing season (higher latitudes), as detailed in Example 12.Gas-exchange measurements of photosynthetic performance at varying CO₂and light levels are performed on the leaves of comparable fullyexpanded leaves from younger plants during their exponential growthphase (20-30 cm tall). The photosynthetic rates are quantified relativeto Rubisco active-site content in the assayed leaves.

As demonstrated by the models in Example 12, and reported in theliterature (Parry et al., 2005), improved photosynthesis may be obtainedin different limiting growth conditions by different mutant Rubiscophenotypes.

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1. A method of generating a Rubisco protein with an improved functionalproperty, the method comprising: (a) identifying at least one Targetamino acid Residue in a first Rubisco protein, wherein said Target aminoacid Residue is associated with said functional property; (b) comparingat least one homologous second Rubisco protein from the same or adifferent phylogenetic branch as the first Rubisco protein with thefirst Rubisco protein and identifying at least one Variant amino acidResidue between the first Rubisco protein and the second Rubiscoprotein; (c) selecting at least one Candidate amino acid Residue fromthe Variant amino acid Residues identified in (b) on the basis of saidCandidate amino acid Residue affecting said Target amino acid Residuewith respect to said functional property; (d) forming at least oneCandidate Mutant protein in silico or producing at least one CandidateMutant protein in vitro in which said at least one Candidate amino acidResidue from the second Rubisco protein substitutes a correspondingresidue in the first Rubisco protein; and (e) screening said at leastone Candidate Mutant Rubisco protein produced in (d) to identify aRubisco protein having said improved functional property.
 2. The methodaccording to claim 1, wherein step (a) and step (b) are performedsimultaneously or wherein step (b) is performed before step (a).
 3. Themethod according to claim 1, wherein step (d) comprises forming orproducing at least one Candidate Mutant Rubisco protein in which the atleast one Candidate amino acid Residue from the second Rubisco proteinis a corresponding residue in a protein or in proteins homologous toRubisco.
 4. The method according to claim 1, wherein step (d) comprisesforming or producing at least one Candidate Mutant Rubisco protein inwhich at least two Candidate amino acid Residues from the second Rubiscoprotein substitute corresponding residues in the first Rubisco proteinand/or in a homologous protein other than the first Rubisco protein. 5.The method according to claim 1, wherein the improved functionalproperty is improved carboxylation efficiency, improved k^(c) _(cat),improved K_(c), improved specificity (S_(c/o)), or improved temperaturedependence.
 6. The method according to claim 1, wherein the Target aminoacid Residues of the Rubisco protein are selected from the groupconsisting of Glu60, Asn123, Lys175, LYS177, KCX201, Asp203, Glu204,His294 and Lys334, which directly coordinate with the reaction centre.7. The method according to claim 1, wherein the Target amino acidResidues of the Rubisco protein are in the N-terminal domain of theRubisco Large subunit.
 8. The method according to claim 1, wherein step(c) comprises selecting at least one Divergent Candidate amino acidResidue or at least one Alternative Candidate amino acid residue,instead of at least one Candidate amino acid Residue, from the Variantamino acid Residues identified in (b).
 9. The method according to claim1, wherein step (c) comprises selecting at least one AlternativeCandidate amino acid Residue and at least one Divergent Candidate aminoacid Residue instead of at least two Candidate amino acid Residues, fromthe Variant amino acid Residues identified in (b).
 10. The methodaccording to claim 1, wherein the step (c) of selecting at least oneCandidate amino acid Residue comprises identifying changes between saidfirst protein and said second protein with respect to electrostaticand/or hydrophobic interactions of the one or more Variant amino acidResidue identified in (b) with the at least one Target amino acidResidue identified in (a) and/or a secondary structural unit whichcontains the at least one Target Residue identified in step (a).
 11. Themethod according to claim 1, wherein the residues of the second Rubiscoprotein used for comparison with the first Rubisco protein comprise allresidues directly coordinated to the active site of a Rubisco protein,all residues interacting with the reactive centre of the substrate orintermediate reaction species of a Rubisco protein, and other residueswithin a proximate distance from the active site of a Rubisco protein ora subset of such residues.
 12. The method according to claim 11, whereinthe proximate distance is between 3 and 28 Å from any atom of substrateor intermediate reaction species.
 13. The method according to claim 1,wherein the first Rubisco protein is taken from species of green plants,flowering plants or cyanobacteria and the second Rubisco protein istaken from species of red algae.
 14. A Rubisco protein produced by themethod according to claim
 1. 15. A Rubisco protein which comprises thesequence as set forth in any one of SEQ ID NOS: 26, 28, 30, 32, 34, 36,38, 40, 42, 44, 46, 48, 50, 52, 54, 56, 58, 60, 62, 64, 66, 68, 70, 74,76, 78, 80, or a functional equivalent thereof, or which is encoded by apolynucleotide comprising the sequence set forth in any one of SEQ IDNOS: 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57,59, 61, 63, 65, 67, 69, 73, 75, 77, 79, or a functional equivalentthereof.
 16. A Rubisco large subunit polypeptide comprising one aminoacid residue substitution or a combination of amino acid residuesubstitutions selected from the group consisting of (Y25W, D51I), (Y25W,D51V), (T23G, K81R), (G54A, C84A, 187V), (G54S, C84A, 187V), (T23G,Y25W, D51I, K81R), (T23G, Y25W, E51I, K81R), (Y25W, D51I, G54A, C84A,187V), (Y25W, D51I, G54S, C84A, 187V), (Y25W, D51V, G54A, C84A, 187V),(V121I, M297G, V300T), (L36I, I116L, F140L), (L36I, I116L, V121I, F140L,M297G, V300T), (K₁₈I, T23G), (K21A, L22K, (gap)M, T23G, Y25W), (T23G,K18I, T68V, K81R), (T23G, K81R, P104E), (T23G, D19P, K81R), (T23G, K81R,V121I, M297G, V300T), (T23G), (K81R), (V121I, M297G), (M297G), and(V121I).
 17. A polynucleotide encoding the Rubisco large subunitpolypeptide according to claim 16 or encoding a Rubisco polypeptidewhich comprises the sequence as set forth in any one of SEQ ID NOS: 26,28, 30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 50, 52, 54, 56, 58, 60, 62,64, 66, 68, 70, 74, 76, 78 or
 80. 18. A vector comprising thepolynucleotide sequence according to claim 17 or a polynucleotidesequence comprising the sequence set forth in any one of SEQ ID NOS: 25,27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61,63, 65, 67, 69, 73, 75, 77, or
 79. 19. A host cell transformed with thepolynucleotide according to claim 17 or with a polynucleotide comprisingthe sequence set forth in any one of SEQ ID NOS: 25, 27, 29, 31, 33, 35,37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 73,75, 77, or
 79. 20. A photosynthetic organism transformed with the vectoraccording to claim 18, a polynucleotide sequence according to claim 17or a polynucleotide sequence comprising the sequence set forth in anyone of SEQ ID NOS: 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49,51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 73, 75, 77, or 79.